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Title Page
Copyright and Credits
Apache Spark Deep Learning Cookbook
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Foreword
Contributors
About the authors
About the reviewers
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
Conventions used
Sections
Getting ready
How to do it...
How it works...
There's more...
See also
Get in touch
Reviews
Setting Up Spark for Deep Learning Development
Introduction
Downloading an Ubuntu Desktop image
Getting ready
How to do it...
How it works...
There's more...
See also
Installing and configuring Ubuntu with VMWare Fusion on macOS
Getting ready
How to do it...
How it works...
There's more...
See also
Installing and configuring Ubuntu with Oracle VirtualBox on Windows
Getting ready
How to do it...
How it works...
There's more...
See also
Installing and configuring Ubuntu Desktop for Google Cloud Platform
Getting ready
How to do it...
How it works...
There's more...
See also
Installing and configuring Spark and prerequisites on Ubuntu Desktop
Getting ready
How to do it...
How it works...
There's more...
See also
Integrating Jupyter notebooks with Spark
Getting ready
How to do it...
How it works...
There's more...
See also
Starting and configuring a Spark cluster
Getting ready
How to do it...
How it works...
There's more...
See also
Stopping a Spark cluster
How to do it...
How it works...
There's more...
Creating a Neural Network in Spark
Introduction
Creating a dataframe in PySpark
Getting ready
How to do it...
How it works...
There's more...
See also
Manipulating columns in a PySpark dataframe
Getting ready
How to do it...
How it works...
There's more...
Converting a PySpark dataframe to an array
Getting ready
How to do it...
How it works...
There's more...
See also
Visualizing an array in a scatterplot
Getting ready
How to do it...
How it works...
There's more...
See also
Setting up weights and biases for input into the neural network
Getting ready
How to do it...
How it works...
There's more...
See also
Normalizing the input data for the neural network
Getting ready
How to do it...
How it works...
See also
Validating array for optimal neural network performance
Getting ready
How to do it...
How it works...
There's more...
See also
Setting up the activation function with sigmoid
Getting ready
How to do it...
How it works...
See also
Creating the sigmoid derivative function
Getting ready
How to do it...
How it works...
See also
Calculating the cost function in a neural network
Getting ready
How to do it...
How it works...
There's more...
See also
Predicting gender based on height and weight
Getting ready
How to do it...
How it works...
See also
Visualizing prediction scores
Getting ready
How to do it...
How it works...
Pain Points of Convolutional Neural Networks
Introduction
Pain Point #1: Importing MNIST images
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Point #2: Visualizing MNIST images
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Point #3: Exporting MNIST images as files
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Point #4: Augmenting MNIST images
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Point #5: Utilizing alternate sources for trained images
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Point #6: Prioritizing high-level libraries for CNNs
Getting ready
How to do it...
How it works...
There's more...
See also
Pain Points of Recurrent Neural Networks
Introduction
Introduction to feedforward networks
Getting ready
How to do it...
How it works...
There's more...
See also
Sequential workings of RNNs
Getting ready
How to do it...
How it works...
There's more...
See also
Pain point #1 – The vanishing gradient problem
Getting ready
How to do it...
How it works...
There's more...
See also
Pain point #2 – The exploding gradient problem
Getting ready
How to do it...
How it works...
There's more...
See also
Sequential working of LSTMs
Getting ready
How to do it...
How it works...
There's more...
See also
Predicting Fire Department Calls with Spark ML
Introduction
Downloading the San Francisco fire department calls dataset
Getting ready
How to do it...
How it works...
There's more...
See also
Identifying the target variable of the logistic regression model
Getting ready
How to do it...
How it works...
There's more...
See also
Preparing feature variables for the logistic regression model
Getting ready
How to do it...
How it works...
There's more...
See also
Applying the logistic regression model
Getting ready
How to do it...
How it works...
There's more...
See also
Evaluating the accuracy of the logistic regression model
Getting ready
How to do it...
How it works...
There's more...
See also
Using LSTMs in Generative Networks
Introduction
Downloading novels/books that will be used as input text
Getting ready
How to do it...
How it works...
There's more...
See also
Preparing and cleansing data
Getting ready
How to do it...
How it works...
See also
Tokenizing sentences
Getting ready
How to do it...
How it works...
There's more...
Training and saving the LSTM model
Getting ready
How to do it...
How it works...
There's more...
See also
Generating similar text using the model
Getting ready
How to do it...
How it works...
There's more...
See also
Natural Language Processing with TF-IDF
Introduction
Downloading the therapy bot session text dataset
Getting ready
How it works...
How to do it...
There's more...
Analyzing the therapy bot session dataset
Getting ready
How to do it...
How it works...
Visualizing word counts in the dataset
Getting ready
How to do it...
How it works...
See also
Calculating sentiment analysis of text
Getting ready
How to do it...
How it works...
See also
Removing stop words from the text
Getting ready
How to do it...
How it works...
See also
Training the TF-IDF model
Getting ready
How to do it...
How it works...
There's more...
See also
Evaluating TF-IDF model performance
Getting ready
How to do it...
How it works...
See also
Comparing model performance to a baseline score
How to do it...
How it works...
See also
Real Estate Value Prediction Using XGBoost
Downloading the King County House sales dataset
Getting ready
How to do it...
How it works...
There's more...
See also
Performing exploratory analysis and visualization
Getting ready
How to do it...
How it works...
There's more...
See also
Plotting correlation between price and other features
Getting ready
How to do it...
How it works...
There's more...
See also
Predicting the price of a house
Getting ready
How to do it...
How it works...
There's more...
See also
Predicting Apple Stock Market Cost with LSTM
Downloading stock market data for Apple
Getting ready
How to do it...
How it works...
There's more...
See also
Exploring and visualizing stock market data for Apple
Getting ready
How to do it...
How it works...
There's more...
See also
Preparing stock data for model performance
Getting ready
How to do it...
How it works...
There's more...
See also
Building the LSTM model
Getting ready
How to do it...
How it works...
See also
Evaluating the model
Getting ready
How to do it...
How it works...
See also
Face Recognition Using Deep Convolutional Networks
Introduction
Downloading and loading the MIT-CBCL dataset into the memory
Getting ready
How to do it...
How it works...
There's more...
See also
Plotting and visualizing images from the directory
Getting ready
How to do it...
How it works...
There's more...
See also
Preprocessing images
Getting ready
How to do it...
How it works...
There's more...
See also
Model building, training, and analysis
Getting ready
How to do it...
How it works...
There's more...
See also
Creating and Visualizing Word Vectors Using Word2Vec
Introduction
Acquiring data
Getting ready
How to do it...
How it works...
There's more...
See also
Importing the necessary libraries
Getting ready
How to do it...
How it works...
There's more...
See also
Preparing the data
Getting ready
How to do it...
How it works...
There's more...
See also
Building and training the model
Getting ready
How to do it...
How it works...
There's more...
See also
Visualizing further
Getting ready
How to do it...
How it works...
See also
Analyzing further
Getting ready
How to do it...
How it works...
See also
Creating a Movie Recommendation Engine with Keras
Introduction
Downloading MovieLens datasets
Getting ready
How to do it...
How it works...
There's more...
See also
Manipulating and merging the MovieLens datasets
Getting ready
How to do it...
How it works...
There's more...
See also
Exploring the MovieLens datasets
Getting ready
How to do it...
How it works...
There's more...
See also
Preparing dataset for the deep learning pipeline
Getting ready
How to do it...
How it works...
There's more...
See also
Applying the deep learning model with Keras
Getting ready
How to do it...
How it works...
There's more...
See also
Evaluating the recommendation engine's accuracy
Getting ready
How to do it...
How it works...
See also
Image Classification with TensorFlow on Spark
Introduction
Downloading 30 images each of Messi and Ronaldo
Getting ready
How to do it...
How it works...
There's more...
See also
Configuring PySpark installation with deep learning packages
Getting ready
How to do it...
How it works...
There's more...
See also
Loading images on to PySpark dataframes
Getting ready
How to do it...
How it works...
There's more...
See also
Understanding transfer learning
Getting ready
How to do it...
How it works...
There's more...
See also
Creating a pipeline for image classification training
Getting ready
How to do it...
How it works...
There's more...
See also
Evaluating model performance
Getting ready
How to do it...
How it works...
There's more...
See also
Fine-tuning model parameters
Getting ready
How to do it...
How it works...
There's more...
See also
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