Apache Spark Deep Learning Cookbook · Over 80 recipes that streamline deep learning in a distributed environment with Apache Spark by Sherif, Ahmed -- Read -- Imperial Library of Trantor

Index

Title Page Copyright and Credits

Apache Spark Deep Learning Cookbook

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Foreword Contributors

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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

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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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