Sherif / Ravindra Apache Spark Deep Learning Cookbook

Over 80 best practice recipes for the distributed training and deployment of neural networks using Keras and TensorFlow
1. Auflage 2018
ISBN: 978-1-78847-155-8
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 474 Seiten

No detailed description available for "Apache Spark Deep Learning Cookbook".

Autoren/Hrsg.

Sherif, Ahmed

Ravindra, Amrith

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Table of Contents - 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

Über Autor(innen)

Sherif Ahmed:

Ahmed Sherif is a data scientist who has worked with data in various roles since 2005. He started off with BI solutions and transitioned to data science in 2013. In 2016, he obtained a master's in Predictive Analytics from Northwestern University, where he studied the science and application of machine learning and predictive modeling using both Python and R. Lately, he has been developing machine learning and deep learning solutions on the cloud using Azure. In 2016, he published his first book, Practical Business Intelligence. He currently works as a Technology Solution Profession in Data and AI for Microsoft.Ravindra Amrith:

Amrith Ravindra is a machine learning enthusiast who holds degrees in electrical and industrial engineering. While pursuing his masters, he dove deeper into the world of machine learning and developed a love for data science. Graduate-level courses in engineering gave him the mathematical background to launch himself into a career in machine learning. He met Ahmed Sherif at a local data science meetup in Tampa. They decided to put their brains together to write a book on their favorite machine learning algorithms. He hopes this book will help him achieve his ultimate goal of becoming a data scientist and actively contributing to machine learning.