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Python Machine Learning Cookbook电子书

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作       者:Giuseppe Ciaburro

出  版  社:Packt Publishing

出版时间:2019-03-30

字       数:65.8万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features * Learn and implement machine learning algorithms in a variety of real-life scenarios * Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques * Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn * Use predictive modeling and apply it to real-world problems * Explore data visualization techniques to interact with your data * Learn how to build a recommendation engine * Understand how to interact with text data and build models to analyze it * Work with speech data and recognize spoken words using Hidden Markov Models * Get well versed with reinforcement learning, automated ML, and transfer learning * Work with image data and build systems for image recognition and biometric face recognition * Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.
目录展开

About Packt

Why subscribe?

Packt.com

Contributors

About the author

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Sections

Getting ready

How to do it…

How it works…

There's more…

See also

Get in touch

Reviews

The Realm of Supervised Learning

Technical requirements

Introduction

Array creation in Python

Getting ready

How to do it…

How it works…

There's more...

See also

Data preprocessing using mean removal

Getting ready

How to do it...

How it works...

There's more...

See also

Data scaling

Getting ready

How to do it...

How it works...

There's more...

See also

Normalization

Getting ready

How to do it...

How it works...

There's more...

See also

Binarization

Getting ready

How to do it...

How it works...

There's more...

See also

One-hot encoding

Getting ready

How to do it...

How it works...

There's more...

See also

Label encoding

Getting ready

How to do it…

How it works...

There's more...

See also

Building a linear regressor

Getting ready

How to do it…

How it works...

There's more...

See also

Computing regression accuracy

Getting ready

How to do it…

How it works...

There's more...

See also

Achieving model persistence

Getting ready

How to do it…

How it works...

There's more...

See also

Building a ridge regressor

Getting ready

How to do it…

How it works...

See also

Building a polynomial regressor

Getting ready

How to do it…

How it works...

There's more...

See also

Estimating housing prices

Getting ready

How to do it…

How it works...

There's more...

See also

Computing the relative importance of features

Getting ready

How to do it…

How it works...

There's more...

See also

Estimating bicycle demand distribution

Getting ready

How to do it…

How it works...

There's more…

See also

Constructing a Classifier

Technical requirements

Introduction

Building a simple classifier

Getting ready

How to do it…

How it works...

There's more…

See also

Building a logistic regression classifier

Getting ready

How to do it…

How it works...

There's more...

See also

Building a Naive Bayes classifier

Getting ready

How to do it…

How it works...

There's more...

See also

Splitting a dataset for training and testing

Getting ready

How to do it…

How it works...

There's more...

See also

Evaluating accuracy using cross-validation metrics

Getting ready…

How to do it…

How it works...

There's more...

See also

Visualizing a confusion matrix

Getting ready

How to do it…

How it works...

There's more...

See also

Extracting a performance report

Getting ready

How to do it…

How it works...

There's more...

See also

Evaluating cars based on their characteristics

Getting ready

How to do it…

How it works...

There's more...

See also

Extracting validation curves

Getting ready

How to do it…

How it works...

There's more...

See also

Extracting learning curves

Getting ready

How to do it…

How it works...

There's more...

See also

Estimating the income bracket

Getting ready

How to do it…

How it works...

There's more...

See also

Predicting the quality of wine

Getting ready

How to do it…

How it works...

There's more...

See also

Newsgroup trending topics classification

Getting ready

How to do it…

How it works...

There's more...

See also

Predictive Modeling

Technical requirements

Introduction

Building a linear classifier using SVMs

Getting ready

How to do it...

How it works...

There's more…

See also

Building a nonlinear classifier using SVMs

Getting ready

How to do it...

How it works...

There's more…

See also

Tackling class imbalance

Getting ready

How to do it...

How it works...

There's more…

See also

Extracting confidence measurements

Getting ready

How to do it...

How it works...

There's more…

See also

Finding optimal hyperparameters

Getting ready

How to do it...

How it works...

The grid search algorithm

The randomized search algorithm

The Bayesian optimization algorithm

There's more…

See also

Building an event predictor

Getting ready

How to do it...

How it works...

There's more…

See also

Estimating traffic

Getting ready

How to do it...

How it works...

There's more…

See also

Simplifying machine learning workflow using TensorFlow

Getting ready

How to do it...

How it works...

There's more…

See also

Implementing a stacking method

Getting ready

How to do it...

How it works...

There's more…

See also

Clustering with Unsupervised Learning

Technical requirements

Introduction

Clustering data using the k-means algorithm

Getting ready

How to do it...

How it works...

There's more…

See also

Compressing an image using vector quantization

Getting ready

How to do it...

How it works...

There's more…

See also

Grouping data using agglomerative clustering

Getting ready

How to do it...

How it works...

There's more…

See also

Evaluating the performance of clustering algorithms

Getting ready

How to do it...

How it works...

There's more…

See also

Estimating the number of clusters using the DBSCAN algorithm

Getting ready

How to do it...

How it works...

There's more…

See also

Finding patterns in stock market data

Getting ready

How to do it...

How it works...

There's more…

See also

Building a customer segmentation model

Getting ready

How to do it...

How it works...

There's more…

See also

Using autoencoders to reconstruct handwritten digit images

Getting ready

How to do it...

How it works...

There's more…

See also

Visualizing Data

Technical requirements

An introduction to data visualization

Plotting three-dimensional scatter plots

Getting ready

How to do it...

How it works...

There's more...

See also

Plotting bubble plots

Getting ready

How to do it...

How it works...

There's more...

See also

Animating bubble plots

Getting ready

How to do it...

How it works...

There's more...

See also

Drawing pie charts

Getting ready

How to do it...

How it works...

There's more...

See also

Plotting date-formatted time series data

Getting ready

How to do it...

How it works...

There's more...

See also

Plotting histograms

Getting ready

How to do it...

How it works...

There's more...

See also

Visualizing heat maps

Getting ready

How to do it...

How it works...

There's more...

See also

Animating dynamic signals

Getting ready

How to do it...

How it works...

There's more...

See also

Working with the Seaborn library

Getting ready

How to do it...

How it works...

There's more...

See also

Building Recommendation Engines

Technical requirements

Introducing the recommendation engine

Building function compositions for data processing

Getting ready

How to do it...

How it works...

There's more...

See also

Building machine learning pipelines

Getting ready

How to do it...

How it works...

There's more...

See also

Finding the nearest neighbors

Getting ready

How to do it...

How it works...

There's more...

See also

Constructing a k-nearest neighbors classifier

Getting ready

How to do it...

How it works...

There's more...

See also

Constructing a k-nearest neighbors regressor

Getting ready

How to do it...

How it works...

There's more...

See also

Computing the Euclidean distance score

Getting ready

How to do it...

How it works...

There's more...

See also

Computing the Pearson correlation score

Getting ready

How to do it...

How it works...

There's more...

See also

Finding similar users in the dataset

Getting ready

How to do it...

How it works...

There's more...

See also

Generating movie recommendations

Getting ready

How to do it...

How it works...

There's more...

See also

Implementing ranking algorithms

Getting ready

How to do it...

How it works...

There's more...

See also

Building a filtering model using TensorFlow

Getting ready

How to do it...

How it works...

There's more...

See also

Analyzing Text Data

Technical requirements

Introduction

Preprocessing data using tokenization

Getting ready

How to do it...

How it works...

There's more...

See also

Stemming text data

Getting ready

How to do it...

How it works...

There's more...

See also

Converting text to its base form using lemmatization

Getting ready

How to do it...

How it works...

There's more...

See also

Dividing text using chunking

How to do it...

How it works...

There's more...

See also

Building a bag-of-words model

Getting ready

How to do it...

How it works...

There's more...

See also

Building a text classifier

Getting ready

How to do it...

How it works...

There's more...

See also

Identifying the gender of a name

Getting ready

How to do it...

How it works...

There's more...

See also

Analyzing the sentiment of a sentence

Getting ready

How to do it...

How it works...

There's more...

See also

Identifying patterns in text using topic modeling

Getting ready

How to do it...

How it works...

There's more...

See also

Parts of speech tagging with spaCy

Getting ready

How to do it...

How it works...

There's more...

See also

Word2Vec using gensim

Getting ready

How to do it...

How it works...

There's more...

See also

Shallow learning for spam detection

Getting ready

How to do it...

How it works...

There's more...

See also

Speech Recognition

Technical requirements

Introducing speech recognition

Reading and plotting audio data

Getting ready

How to do it...

How it works...

There's more...

See also

Transforming audio signals into the frequency domain

Getting ready

How to do it...

How it works...

There's more...

See also

Generating audio signals with custom parameters

Getting ready

How to do it...

How it works...

There's more...

See also

Synthesizing music

Getting ready

How to do it...

How it works...

There's more...

See also

Extracting frequency domain features

Getting ready

How to do it...

How it works...

There's more...

See also

Building HMMs

Getting ready

How to do it...

How it works...

There's more...

See also

Building a speech recognizer

Getting ready

How to do it...

How it works...

There's more...

See also

Building a TTS system

Getting ready

How to do it...

How it works...

There's more...

See also

Dissecting Time Series and Sequential Data

Technical requirements

Introducing time series

Transforming data into a time series format

Getting ready

How to do it...

How it works...

There's more…

See also

Slicing time series data

Getting ready

How to do it...

How it works...

There's more…

See also

Operating on time series data

Getting ready

How to do it...

How it works...

There's more…

See also

Extracting statistics from time series data

Getting ready

How to do it...

How it works...

There's more…

See also

Building HMMs for sequential data

Getting ready

How to do it...

How it works...

There's more…

See also

Building CRFs for sequential text data

Getting ready

How to do it...

How it works...

There's more…

See also

Analyzing stock market data

Getting ready

How to do it...

How it works...

There's more…

See also

Using RNNs to predict time series data

Getting ready

How to do it...

How it works...

There's more…

See also

Analyzing Image Content

Technical requirements

Introducing computer vision

Operating on images using OpenCV-Python

Getting ready

How to do it...

How it works...

There's more…

See also

Detecting edges

Getting ready

How to do it...

How it works...

There's more…

See also

Histogram equalization

Getting ready

How to do it...

How it works...

There's more…

See also

Detecting corners

Getting ready

How to do it...

How it works...

There's more…

See also

Detecting SIFT feature points

Getting ready

How to do it...

How it works...

There's more…

See also

Building a Star feature detector

Getting ready

How to do it...

How it works...

There's more…

See also

Creating features using Visual Codebook and vector quantization

Getting ready

How to do it...

How it works...

There's more…

See also

Training an image classifier using Extremely Random Forests

Getting ready

How to do it...

How it works...

There's more…

See also

Building an object recognizer

Getting ready

How to do it...

How it works...

There's more…

See also

Using Light GBM for image classification

Getting ready

How to do it...

How it works...

There's more…

See also

Biometric Face Recognition

Technical requirements

Introduction

Capturing and processing video from a webcam

Getting ready

How to do it...

How it works...

There's more…

See also

Building a face detector using Haar cascades

Getting ready

How to do it...

How it works...

There's more…

See also

Building eye and nose detectors

Getting ready

How to do it...

How it works...

There's more…

See also

Performing principal component analysis

Getting ready

How to do it...

How it works...

There's more…

See also

Performing kernel principal component analysis

Getting ready

How to do it...

How it works...

There's more…

See also

Performing blind source separation

Getting ready

How to do it...

How it works...

There's more…

See also

Building a face recognizer using a local binary patterns histogram

Getting ready

How to do it...

How it works...

There's more…

See also

Recognizing faces using the HOG-based model

Getting ready

How to do it...

How it works...

There's more…

See also

Facial landmark recognition

Getting ready

How to do it...

How it works...

There's more…

See also

User authentication by face recognition

Getting ready

How to do it...

How it works...

There's more…

See also

Reinforcement Learning Techniques

Technical requirements

Introduction

Weather forecasting with MDP

Getting ready

How to do it…

How it works…

There's more…

See also

Optimizing a financial portfolio using DP

Getting ready

How to do it…

How it works…

There's more…

See also

Finding the shortest path

Getting ready

How to do it…

How it works…

There's more…

See also

Deciding the discount factor using Q-learning

Getting ready

How to do it…

How it works…

There's more…

See also

Implementing the deep Q-learning algorithm

Getting ready

How to do it…

How it works…

There's more…

See also

Developing an AI-based dynamic modeling system

Getting ready

How to do it…

How it works…

There's more…

See also

Deep reinforcement learning with double Q-learning

Getting ready

How to do it…

How it works…

There's more…

See also

Deep Q-network algorithm with dueling Q-learning

Getting ready

How to do it…

How it works…

There's more…

See also

Deep Neural Networks

Technical requirements

Introduction

Building a perceptron

Getting ready

How to do it...

How it works...

There's more…

See also

Building a single layer neural network

Getting ready

How to do it...

How it works...

There's more…

See also

Building a deep neural network

Getting ready

How to do it...

How it works...

There's more…

See also

Creating a vector quantizer

Getting ready

How to do it...

How it works...

There's more…

See also

Building a recurrent neural network for sequential data analysis

Getting ready

How to do it...

How it works...

There's more…

See also

Visualizing the characters in an OCR database

Getting ready

How to do it...

How it works...

There's more…

See also

Building an optical character recognizer using neural networks

Getting ready

How to do it...

How it works...

There's more…

See also

Implementing optimization algorithms in ANN

Getting ready

How to do it...

How it works...

There's more…

See also

Unsupervised Representation Learning

Technical requirements

Introduction

Using denoising autoencoders to detect fraudulent transactions

Getting ready

How to do it…

How it works...

There's more…

See also

Generating word embeddings using CBOW and skipgram representations

Getting ready

How to do it…

How it works...

There's more…

See also

Visualizing the MNIST dataset using PCA and t-SNE

Getting ready

How to do it…

How it works...

There's more…

See also

Using word embedding for Twitter sentiment analysis

Getting ready

How to do it…

How it works...

There's more…

See also

Implementing LDA with scikit-learn

Getting ready

How to do it…

How it works...

There's more…

See also

Using LDA to classify text documents

Getting ready

How to do it…

How it works...

There's more…

See also

Preparing data for LDA

Getting ready

How to do it...

How it works...

There's more…

See also

Automated Machine Learning and Transfer Learning

Technical requirements

Introduction

Working with Auto-WEKA

Getting ready

How to do it...

How it works...

There's more…

See also

Using AutoML to generate machine learning pipelines with TPOT

Getting ready

How to do it...

How it works...

There's more…

See also

Working with Auto-Keras

Getting ready

How to do it...

How it works...

There's more…

See also

Working with auto-sklearn

Getting ready

How to do it...

How it works...

There's more…

See also

Using MLBox for selection and leak detection

Getting ready

How to do it...

How it works...

There's more…

See also

Convolutional neural networks with transfer learning

Getting ready

How to do it...

How it works...

There's more…

See also

Transfer learning with pretrained image classifiers using ResNet-50

Getting ready

How to do it...

How it works...

There's more…

See also

Transfer learning using feature extraction with the VGG16 model

Getting ready

How to do it...

How it works...

There's more…

See also

Transfer learning with pretrained GloVe embedding

Getting ready

How to do it...

How it works...

There's more…

Inductive transfer learning

Unsupervised transfer learning

Transductive transfer learning

Instance transfer learning

See also

Unlocking Production Issues

Technical requirements

Introduction

Handling unstructured data

Getting ready

How to do it...

How it works...

There's more…

See also

Deploying machine learning models

Getting ready

How to do it...

How it works...

There's more…

See also

Keeping track of changes into production

How to do it...

How it works...

There's more…

See also

Tracking accuracy to optimize model scaling

How to do it...

How it works...

There's more…

See also

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