Find out how to write Kotlin code without overhead and how to use different profiling tools and bytecode viewer to inspect expressions of Kotlin language. About This Book ? Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes. ? Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance. ? Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues. Who This Book Is For This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed. What You Will Learn ? Understand the importance of high performance ? Learn performance metrics ? Learn popular design patterns currently being used in Kotlin ? Understand how to apply modern Kotlin features to data processing ? Learn how to use profling tools ? Discover how to read bytecode ? Learn to perform memory optimizations ? Uncover approaches to the multithreading environment In Detail The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment Style and approach This book guides you through how to use profiling tools to detect performance issues and build high-performance applications in the Kotlin environment.

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. About This Book ? Explore deep reinforcement learning (RL), from the first principles to the latest algorithms ? Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms ? Keep up with the very latest industry developments, including AI-driven chatbots Who This Book Is For Some fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL. What You Will Learn ? Understand the DL context of RL and implement complex DL models ? Learn the foundation of RL: Markov decision processes ? Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others ? Discover how to deal with discrete and continuous action spaces in various environments ? Defeat Atari arcade games using the value iteration method ? Create your own OpenAI Gym environment to train a stock trading agent ? Teach your agent to play Connect4 using AlphaGo Zero ? Explore the very latest deep RL research on topics including AI-driven chatbots In Detail Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. Style and approach Deep Reinforcement Learning Hands-On explains the art of building self-learning agents using algorithms and practical examples. Experiment with famous examples, such as Google's defeat of well-known Atari arcade games.

Develop efficient and modern full-stack applications using Spring Boot and React 16 About This Book ? Develop resourceful backends using Spring Boot and faultless frontends using React. ? Explore the techniques involved in creating a full-stack app by going through a methodical approach. ? Learn to add CRUD functionalities and use Material UI in the user interface to make it more user-friendly. Who This Book Is For Java developers who are familiar with Spring, but have not yet built full-stack applications What You Will Learn ? Create a RESTful web service with Spring Boot ? Understand how to use React for frontend programming ? Gain knowledge of how to create unit tests using JUnit ? Discover the techniques that go into securing the backend using Spring Security ? Learn how to use Material UI in the user interface to make it more user-friendly ? Create a React app by using the Create React App starter kit made by Facebook In Detail Apart from knowing how to write frontend and backend code, a full-stack engineer has to tackle all the problems that are encountered in the application development life cycle, starting from a simple idea to UI design, the technical design, and all the way to implementing, testing, production, deployment, and monitoring. This book covers the full set of technologies that you need to know to become a full-stack web developer with Spring Boot for the backend and React for the frontend. This comprehensive guide demonstrates how to build a modern full-stack application in practice. This book will teach you how to build RESTful API endpoints and work with the data access Layer of Spring, using Hibernate as the ORM. As we move ahead, you will be introduced to the other components of Spring, such as Spring Security, which will teach you how to secure the backend. Then, we will move on to the frontend, where you will be introduced to React, a modern JavaScript library for building fast and reliable user interfaces, and its app development environment and components. You will also create a Docker container for your application. Finally, the book will lay out the best practices that underpin professional full-stack web development. Style and approach A step-by-step guide to building full-stack applications along with best practices to make your Full-stack development journey easier

Run Ansible playbooks to launch complex multi-tier applications hosted in public clouds About This Book ? Build your learning curve using Ansible ? Automate cloud, network, and security infrastructures with ease ? Gain hands-on exposure on Ansible Who This Book Is For Learn Ansible is perfect for system administrators and developers who want to take their current workflows and transform them into repeatable playbooks using Ansible. No prior knowledge of Ansible is required. What You Will Learn ? Write your own playbooks to configure servers running CentOS, Ubuntu, and Windows ? Identify repeatable tasks and write playbooks to automate them ? Define a highly available public cloud infrastructure in code, making it easy to distribute your infrastructure configuration ? Deploy and configure Ansible Tower and Ansible AWX ? Learn to use community contributed roles ? Use Ansible in your day-to-day role and projects In Detail Ansible has grown from a small, open source orchestration tool to a full-blown orchestration and configuration management tool owned by Red Hat. Its powerful core modules cover a wide range of infrastructures, including on-premises systems and public clouds, operating systems, devices, and services—meaning it can be used to manage pretty much your entire end-to-end environment. Trends and surveys say that Ansible is the first choice of tool among system administrators as it is so easy to use. This end-to-end, practical guide will take you on a learning curve from beginner to pro. You'll start by installing and configuring the Ansible to perform various automation tasks. Then, we'll dive deep into the various facets of infrastructure, such as cloud, compute and network infrastructure along with security. By the end of this book, you'll have an end-to-end understanding of Ansible and how you can apply it to your own environments. Style and approach A hands-on approach to give you practical experience of writing playbooks and roles and executing them. At the end of each chapter, you’ll find test questions to test your knowledge on Ansible.

Leverage the power of Apple's Core ML to create smart iOS apps About This Book ? Explore the concepts of machine learning and Apple’s Core ML APIs ? Use Core ML to understand and transform images and videos ? Exploit the power of using CNN and RNN in iOS applications Who This Book Is For Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers. What You Will Learn ? Understand components of an ML project using algorithms, problems, and data ? Master Core ML by obtaining and importing machine learning model, and generate classes ? Prepare data for machine learning model and interpret results for optimized solutions ? Create and optimize custom layers for unsupported layers ? Apply CoreML to image and video data using CNN ? Learn the qualities of RNN to recognize sketches, and augment drawing ? Use Core ML transfer learning to execute style transfer on images In Detail Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of CoreML

Build a solid foundation in coding by utilizing the language and its core characteristics About This Book ? Leverage the features of Python programming through easy-to-follow examples ? Develop a strong set of programming skills that can be applied on all platforms ? Create GUIs and data science-based applications Who This Book Is For Learn Python Programming is for individuals with relatively little experience in coding or Python. It's also ideal for aspiring programmers who need to write scripts or programs to accomplish tasks. The book takes you all the way to creating a full-fledged application. What You Will Learn ? Get Python up and running on Windows, Mac, and Linux ? Grasp fundamental concepts of coding using data structures and control flow ? Write elegant, reusable, and efficient code in any situation ? Understand when to use the functional or object-oriented programming (OOP) approach ? Walk through the basics of security and concurrent/asynchronous programming ? Create bulletproof, reliable software by writing tests ? Explore examples of GUIs, scripting, and data science In Detail Learn Python Programming creates a foundation for those who are interested in developing their skills in Python programming. The book starts with the fundamentals of programming with Python and ends by exploring different topics such as GUIs and real-world apps. You will begin by exploring the foundations of and fundamental topics on Python and learn to manipulate them. Then, you'll explore different programming paradigms that will allow you to find the best approach to a situation, and you’ll also understand how to carry out performance optimization as well as effective debugging. As you make your way through the chapters, you'll control the flow of a program, and persist and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Throughout, the book covers various types of applications, and it concludes with building real-world applications based on all the concepts that you learned. By the end of the book, you'll have a proper understanding of the Python language and a solid grasp on how to work with data. You'll know how to quickly build a website and harness the power of Python's renowned data science libraries. Style and approach This easy-to-follow guide will take you from novice to proficient at a comfortable pace, using a lot of simple yet effective examples.

Build and deploy powerful neural network models using the latest Java deep learning libraries About This Book ? Understand DL with Java by implementing real-world projects ? Master implementations of various ANN models and build your own DL systems ? Develop applications using NLP, image classification, RL, and GPU processing Who This Book Is For If you are a data scientist, machine learning professional, or deep learning practitioner keen to expand your knowledge by delving into the practical aspects of deep learning with Java, then this book is what you need! Get ready to build advanced deep learning models to carry out complex numerical computations. Some basic understanding of machine learning concepts and a working knowledge of Java are required. What You Will Learn ? Master deep learning and neural network architectures ? Build real-life applications covering image classification, object detection, online trading, transfer learning, and multimedia analytics using DL4J and open-source APIs ? Train ML agents to learn from data using deep reinforcement learning ? Use factorization machines for advanced movie recommendations ? Train DL models on distributed GPUs for faster deep learning with Spark and DL4J ? Ease your learning experience through 69 FAQs In Detail Java is one of the most widely used programming languages. With the rise of deep learning, it has become a popular choice of tool among data scientists and machine learning experts. Java Deep Learning Projects starts with an overview of deep learning concepts and then delves into advanced projects. You will see how to build several projects using different deep neural network architectures such as multilayer perceptrons, Deep Belief Networks, CNN, LSTM, and Factorization Machines. You will get acquainted with popular deep and machine learning libraries for Java such as Deeplearning4j, Spark ML, and RankSys and you’ll be able to use their features to build and deploy projects on distributed computing environments. You will then explore advanced domains such as transfer learning and deep reinforcement learning using the Java ecosystem, covering various real-world domains such as healthcare, NLP, image classification, and multimedia analytics with an easy-to-follow approach. Expert reviews and tips will follow every project to give you insights and hacks. By the end of this book, you will have stepped up your expertise when it comes to deep learning in Java, taking it beyond theory and be able to build your own advanced deep learning systems. Style and approach A unique, learn-as-you-do approach, as the reader builds on his understanding of deep learning with Java progressively with each project. This book is designed in such a way that implementing each project will empower you with a unique skill set, and enable you to implement the next project more confidently.

Learn steps and tasks to help a NetSuite administrator perform both his daily and monthly tasks efficiently. Advance his expertise to become NetSuite leader without having to spend time and money on corporate trainings. About This Book ? Understand the business considerations and implementation of the NetSuite ERP ? Gain a deep knowledge of enterprise security, data management, process automation, and analytics ? Learn techniques to sail through system maintenance while ensuring accuracy and to practically troubleshoot issues Who This Book Is For This book is for administrators, consultants, and Project Managers who would like to improve their skills in the areas of configuration and system management. Basic experience implementing NetSuite is assumed. What You Will Learn ? Provide executives with meaningful insights into the business ? A Framework to streamline the implementation of new and existing features ? Leverage built-in tools to optimize your efficiency and effectiveness ? Test configuration to check the implementation of role-specific permissions ? Understand how to optimize the amount of data to be shared with users ? Import data like new leads and employ current data like pricing updates ? Perform on-going maintenance and troubleshoot issues In Detail NetSuite ERP is a complete, scalable cloud ERP solution targeted at fast-growing, mid-sized businesses and large enterprises. It's the smartly executed combination of financial management operations and built-in business intelligence, which enables companies to make data-driven and well-informed decisions. This book will help administrators become expert enough to be seen as the NetSuite leader at their company and to be able to advise department heads on specific processes, and strategic decisions. We start with an overview of ERP and NetSuite ERP, before going on to explain the built-in features to show the breadth of NetSuite ERP's product and its ease of use. We then discuss business aspects, focusing on the most important processes in NetSuite. Then you'll understand the implementation aspects that are generic enough to cover all the features. The focus then shifts to specific skills that you will need to administer for any system, such as roles, permissions, customization, and data imports. Moving on, you'll learn how to centralize the creation of search templates and give users the tools to pivot the data and expose it to the user in useful ways, such as on the dashboard. The book ends with checklists providing actionable steps that you as an administrator can take to do your job and support the application through new releases and troubleshooting problems. Style and approach A slow and steady introduction of topics from reports through searches with aim to enable the administrator to gain a holistic view of the NetSuite product.

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. About This Book ? Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras ? Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms ? Learn deep learning techniques for text analysis Who This Book Is For This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you! What You Will Learn ? Why text analysis is important in our modern age ? Understand NLP terminology and get to know the Python tools and datasets ? Learn how to pre-process and clean textual data ? Convert textual data into vector space representations ? Using spaCy to process text ? Train your own NLP models for computational linguistics ? Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn ? Employ deep learning techniques for text analysis using Keras In Detail Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. Style and approach The book teaches NLP from the angle of a practitioner as well as that of a student. This is a tad unusual, but given the enormous speed at which new algorithms and approaches travel from scientific beginnings to industrial implementation, first principles can be clarified with the help of entirely practical examples.

Get to grips with the most popular Python packages that make data analysis possible About This Book ? Explore the tools you need to become a data analyst ? Discover practical examples to help you grasp data processing concepts ? Walk through hierarchical indexing and grouping for data analysis Who This Book Is For Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book. What You Will Learn ? Understand how to install and manage Anaconda ? Read, sort, and map data using NumPy and pandas ? Find out how to create and slice data arrays using NumPy ? Discover how to subset your DataFrames using pandas ? Handle missing data in a pandas DataFrame ? Explore hierarchical indexing and plotting with pandas In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. Style and approach A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.

Develop a solid understanding of the important command-line tools and utilities in Linux About This Book ? Delve into the fundamentals of Linux ? Explore and work with virtualization, command lines, and Bash shell scripts ? Use special file permission flags such as setuid and setgid Who This Book Is For Fundamentals of Linux is for individuals looking to work as a Linux system administrator. What You Will Learn ? Explore basic and advanced command-line concepts ? Install Linux, work with VirtualBox, and install CentOS 7 in VirtualBox ? Work with the command line efficiently and learn how to navigate through the Linux filesystem ? Create file and user group permissions and edit files ? Use Sticky bit to secure your Linux filesystem ? Define and remove ACL from Linux files In Detail Linux is a Unix-like operating system assembled under the model of free and open source software development and distribution. Fundamentals of Linux will help you learn all the essentials of the Linux command line required to get you started. The book will start by teaching you how to work with virtualization software and install CentOS 7 Linux as a VM. Then, you will get to grips with the workings of various command line operations, such as cursor movement, commands, options, and arguments. As you make your way through the chapters, the book will not only focus on the most essential Linux commands but also give an introduction to Bash shell scripting. Finally, you will explore advanced topics, such as networking and troubleshooting your system, and you will get familiar with the advanced file permissions: ACL, setuid, and setgid. Fundamentals of Linux includes real-world tasks, use cases, and problems that, as a system administrator, you might encounter in your day-to-day activities. Style and approach A step-by-step guide filled with real-world examples that will cover the fundamentals of Linux

This book will teach you what you need to know to start using GitHub effectively for collaborating and working on your software projects. About This Book ? Effectively use GitHub by learning its key features to leverage the power of Git and make collaboration on code easy to work with. ? Be more productive on the development workflow of your projects using the valuable toolset that GitHub provides. ? Explore the world of GitHub by following simple, step-by-step, real-world scenarios accompanied by helpful, explanatory screenshots. Who This Book Is For This book is for experienced or novice developers with a basic knowledge of Git. If you ever wanted to learn how big projects such as Twitter, Google, or even GitHub collaborate on code, then this book is for you. What You Will Learn ? Create and upload repositories to your account ? Create organizations and manage teams with different access levels on repositories ? Use the issue tracker effectively and add context to issues with labels and milestones ? Create, access, and personalize your user account and profile settings ? Build a community around your project using the sophisticated tools GitHub provides ? Create GitHub pages and understand web analytics In Detail Whether you are an experienced developer or a novice, learning to work with Version Control Systems is a must in the software development world. Git is the most popular tool for that purpose, and GitHub was built around it, leveraging its powers by bringing it to the web. Starting with the basics of creating a repository, you will then learn how to manage the issue tracker, the place where discussions about your project take place. Continuing our journey, we will explore how to use the wiki and write rich documentation that will accompany your project. You will also master organization/team management and some of the features that made GitHub so well known, including pull requests. Next, we will focus on creating simple web pages hosted on GitHub and lastly, we will explore the settings that are configurable for a user and a repository. Style and approach This book will take you through some of the most important features of one of the most popular tools, GitHub, which is used to bring developers together from all around the world to discover, share, and build better software. At each step of the way, you will learn about important approaches used in GitHub, including creating a repository, managing teams, creating GitHub pages, and watching your repository's web analytics, among others.

Discover how you can migrate a traditional on-premise SQL server database to a cloud-based solution with Microsoft Azure. Built with database administrators in mind, this book emulates different scenarios you might come across while working with large, complex SQL database migrations and provides solutions for effectively managing the migrated databases. Key Features *Implement backup, restore, and recovery of Azure SQL databases *Create shards and elastic pools to scale Azure SQL databases *Automate common management tasks with PowerShell *Implement over 40 practical activities and exercises across 24 topics to reinforce your learning Book Description As the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. It’s important to know how to administer SQL Database to fully benefit from all of the features and functionality that it provides. This book addresses important aspects of an Azure SQL Database instance such as migration, backup restorations, pricing policies, security, scalability, monitoring, performance optimization, high availability, and disaster recovery. It is a complete guide for database administrators, and ideal for those who are planning to migrate from on premise SQL Server database to an Azure SQL Server database. What you will learn *Learn how to provision a new database or migrate an existing on-premise solution *Understand how to backup, restore, secure, and scale your own Azure SQL Database *Optimize the performance by monitoring and tuning your cloud-based SQL instance *Implement high availability and disaster recovery procedures with SQL Database *Develop a roadmap for your own scalable cloud solution with Azure SQL Database Who this book is for This book is ideal for database administrators, database developers, or application developers who are interested in developing or migrating existing applications with Azure SQL Database. Prior experience of working with an on-premise SQL Server deployment and brief knowledge of PowerShell and C# are recommended prerequisites.

Bridge the gap between developer and data scientist by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. Key Features *Think deeply as a developer about your strategy and toolset in data science *Discover the best tools that will suit you as a developer in your data analysis *Accelerate the road to data insight as a programmer using Jupyter Notebook *Deep dive into multiple industry data science use cases Book Description Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights. Industry expert David Taieb bridges the gap between developers and data scientists by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. You'll find the right balance of strategic thinking and practical projects throughout this book, with extensive code files and Jupyter projects that you can integrate with your own data analysis. David Taieb introduces four projects designed to connect developers to important industry use cases in data science. The first is an image recognition application with TensorFlow, to meet the growing importance of AI in data analysis. The second analyses social media trends to explore big data issues and natural language processing. The third is a financial portfolio analysis application using time series analysis, pivotal in many data science applications today. The fourth involves applying graph algorithms to solve data problems. Taieb wraps up with a deep look into the future of data science for developers and his views on AI for data science. What you will learn *Bridge the gap between developer and data scientist with a Python-based toolset *Get the most out of Jupyter Notebooks with new productivity-enhancing tools *Explore and visualize data using Jupyter Notebooks and PixieDust *Work with and assess the impact of artificial intelligence in data science *Work with TensorFlow, graphs, natural language processing, and time series *Deep dive into multiple industry data science use cases *Look into the future of data analysis and where to develop your skills Who this book is for This book is for established developers who want to bridge the gap between programmers and data scientists. With the introduction of PixieDust from its creator, the book will also be a great desk companion for the already accomplished Data Scientist. Some fluency in data interpretation and visualization is also assumed since this book addresses data professionals such as business and general data analysts. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. About This Book ? Get up and running with the Jupyter ecosystem and some example datasets ? Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests ? Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is For This book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start. What You Will Learn ? Identify potential areas of investigation and perform exploratory data analysis ? Plan a machine learning classification strategy and train classification models ? Use validation curves and dimensionality reduction to tune and enhance your models ? Scrape tabular data from web pages and transform it into Pandas DataFrames ? Create interactive, web-friendly visualizations to clearly communicate your findings In Detail Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Style and approach This book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

Discover techniques and tools for building serverless applications with AWS Lambda About This Book ? Learn to write, run, and deploy Lambda functions in the AWS cloud ? Make the most of AWS Lambda functions to build scalable and cost-efficient systems ? A practical guide to developing serverless services and applications in Node.js, Java, Python, and C# Who This Book Is For This book is primarily for IT architects and developers who want to build scalable systems and deploy serverless applications with AWS Lambda. No prior knowledge of AWS is necessary. What You Will Learn ? Understand the fundamental concepts of AWS Lambda ? Get to grips with the Serverless Framework and how to create a serverless project ? Testing and debugging Lambda functions ? Create a stateful, serverless backend with DynamoDB ? Program AWS Lambda with Java, Python, and C# ? Program a lambda function with Node.js In Detail AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda. The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity. Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#. Style and approach This book will provide clear instructions that introduce the viewer to programming AWS Lambda with Node.js, Java, Python, and C#. Moreover, readers will learn how to deploy and test Lambda functions, and how to set up and use the serverless framework.

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features * Weave neural networks into linguistic applications across various platforms * Perform NLP tasks and train its models using NLTK and TensorFlow * Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn *Implement semantic embedding of words to classify and find entities *Convert words to vectors by training in order to perform arithmetic operations *Train a deep learning model to detect classification of tweets and news *Implement a question-answer model with search and RNN models *Train models for various text classification datasets using CNN *Implement WaveNet a deep generative model for producing a natural-sounding voice *Convert voice-to-text and text-to-voice *Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Develop modern user interfaces using Angular 6 and its component-based architecture. Key Features * Build better web applications with highly scalable concepts using Angular * Learn new ways to design your web applications * Build a fully functional web application that lets you tackle real-world user interface problems using Angular components Book Description Angular framework embraces a mature user interface (UI) component architecture, a powerful tool when developing scalable application interfaces. The simple and deterministic design of Angular components supports you in building large and scalable component-based applications. Mastering Angular Components covers a new holistic way of thinking about UI development, and helps you discover the power of Angular 6 components through various examples. The book starts with an introduction to component-based user interfaces and how Angular 6 manages this concept. Following a step-by-step approach, you will build a fully functional task-management application using Angular. You’ll start with basic layout components, adding some core task-management components before completing the first draft of your application. You will then move on to working through a refactoring exercise in order to learn how to enhance the way you deal with states and data. Once you have got to grips with all this, you will study how to make use of the Angular router within your application. By the end of this book, you will be able to constantly refine the functionality of your application and create components that render SVG graphics, add a time-tracking feature, visualize data using third-party library Chartist, and even create a plugin architecture using Angular components. What you will learn * Use TypeScript to create Angular 6 components * Leverage component composition to solve complex UI requirements * Build an architecture using pure components and container components * Explore the basics of RxJS observable streams and use them to build your application reactively * Communicate between components using child queries * Implement the Angular router to make your application navigable * Build reusable and dynamic graphical content using Angular components and SVG * Integrate third-party libraries such as Moment.js and Chartist into your existing Angular application Who this book is for Mastering Angular Components is for you if you are an Angular developer who already has a good understanding of basic frontend web technologies such as JavaScript, HTML, and CSS.

Learn everything you need to get up and running with cutting-edge API development using JavaScript and Node.js; ideal for data-intensive real-time applications that run across multiple platforms. Key Features *Build web APIs from start to finish using JavaScript across the development stack *Explore advanced concepts such as authentication with JWT, and running tests against your APIs *Implement over 20 practical activities and exercises across 9 topics to reinforce your learning Book Description Using the same framework to build both server and client-side applications saves you time and money. This book teaches you how you can use JavaScript and Node.js to build highly scalable APIs that work well with lightweight cross-platform client applications. It begins with the basics of Node.js in the context of backend development, and quickly leads you through the creation of an example client that pairs up with a fully authenticated API implementation. By the end of the book, you’ll have the skills and exposure required to get hands-on with your own API development project. What you will learn *Understand how Node.js works, its trends, and where it is being used now *Learn about application modularization and built-in Node.js modules *Use the npm third-party module registry to extend your application *Gain an understanding of asynchronous programming with Node.js *Develop scalable and high-performing APIs using hapi.js and Knex.js *Write unit tests for your APIs to ensure reliability and maintainability Who this book is for This book is ideal for developers who already understand JavaScript and are looking for a quick no-frills introduction to API development with Node.js. Though prior experience with other server-side technologies such as Python, PHP, ASP.NET, Ruby will help, it’s not essential to have a background in backend development before getting started.

Take your web applications to a whole new level with efficient, component-based UIs that deliver cutting-edge interactivity and performance. Key Features *Elaborately explains basics before introducing advanced topics *Explains creating and managing the state of components across applications *Implement over 15 practical activities and exercises across 11 topics to reinforce your learning Book Description Projects like Angular and React are rapidly changing how development teams build and deploy web applications to production. In this book, you’ll learn the basics you need to get up and running with React and tackle real-world projects and challenges. It includes helpful guidance on how to consider key user requirements within the development process, and also shows you how to work with advanced concepts such as state management, data-binding, routing, and the popular component markup that is JSX. As you complete the included examples, you’ll find yourself well-equipped to move onto a real-world personal or professional frontend project. What you will learn *Understand how React works within a wider application stack *Analyze how you can break down a standard interface into specific components *Successfully create your own increasingly complex React components with HTML or JSX *Correctly handle multiple user events and their impact on overall application state *Understand the component lifecycle to optimize the UX of your application *Configure routing to allow effortless, intuitive navigation through your components Who this book is for If you are a frontend developer who wants to create truly reactive user interfaces in JavaScript, then this is the book for you. For React, you’ll need a solid foundation in the essentials of the JavaScript language, including new OOP features that were introduced in ES2015. An understanding of HTML and CSS is assumed, and a basic knowledge of Node.js will be useful in the context of managing a development workflow, but is not essential.

Deploy functions efficiently using different cloud-based serverless offerings Key Features *Understand the concept of Function-as-a-Service *Implement Serverless solutions using AWS Lambda, Azure Functions and Google Cloud Functions *Practical approach towards choosing the best tool for your serverless environment Book Description Serverless applications and architectures are gaining momentum and are increasingly being used by companies of all sizes. Serverless software takes care of many problems that developers face when running systems and servers, such as fault tolerance, centralized logging, horizontal scalability, and deployments. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon finishing the book, you will have the knowledge and resources to build your own serverless application hosted in AWS, Microsoft Azure, or Google Cloud Platform, and will have experienced the benefits of event-driven technology for yourself. This hands-on guide dives into the basis of serverless architectures and how to build them using Node.js as a programming language, Visual Studio Code for code editing, and Postman for quickly and securely developing applications without the hassle of configuring and maintaining infrastructure on three public cloud platforms. What you will learn *Understand the benefts of serverless computing and know when to use it *Develop serverless applications on AWS, Azure, and Google Cloud *Get to grips with Function as a Service (FaaS) *Apply triggers to serverless functions *Build event-driven apps using serverless frameworks *Use the Node.js programming language to build serverless apps *Use code editors, such as Visual Studio Code, as development environments *Master the best development practices for creating scalable and practical solutions Who this book is for This book is targeted towards developers, system administrators or any stakeholder working in the Serverless environment and want to understand how functions work. Basic idea of serverless architecture can be an added advantage