Apache Spark Deep Learning Cookbook
Apache Spark Deep Learning Cookbook presents useful tips and tricks to overcome any problem related to building efficient distributed deep learning applications on Apache Spark. With the help of this book, you will leverage powerful deep learning libraries such as TensorFlow to develop your models and ensure their optimum performance.
Offered by
Difficulty Level
Intermediate
Completion Time
15h48m
Language
English
About Book
Who Is This Book For?
If you’re looking for a practical resource for implementing efficiently distributed deep learning models with Apache Spark, then this book is for you. Knowledge of core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the most out of this book. Some knowledge of Python programming will also be useful.
Apache Spark Deep Learning Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 15h48m total length
Setting Up Spark for Deep Learning Development
Creating a Neural Network in Spark
Pain Points of Convolutional Neural Networks
Pain Points of Recurrent Neural Networks
Predicting Fire Department Calls with Spark ML
Using LSTMs in Generative Networks
Natural Language Processing with TF-IDF
Real Estate Value Prediction using XGBoost
Predicting Apple Stock Market Cost with LSTM
Face Recognition using Deep Convolutional Networks
Creating and Visualizing Word Vectors Using Word2Vec
Creating a Movie Recommendation Engine with Keras
Image Classification with TensorFlow on Spark
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