Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark

Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark

Enregistré dans:

Détails bibliographiques
Auteur principal:	Sherif, Ahmed. (Auteur)
Autres auteurs:	Ravindra, Amrith. (Auteur)
Support:	E-Book
Langue:	Anglais
Publié:	Birmingham : Packt Publishing, 2018.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

Hands-on deep learning with Apache Spark : build and deploy distributed deep learning applications on Apache Spark
par: Iozzia, Guglielmo.
Publié: (2019)

Learning Apache Spark 2
par: Abbasi, Muhammad Asif.
Publié: (2017)

Apache Spark for data science cookbook : over insightful 90 recipes to get lightning-fast analytics with Apache Spark
par: Chitturi, Padma Priya.
Publié: (2017)

Apache Spark 2.x machine learning cookbook
par: Amirghodsi, Siamak.
Publié: (2017)

Apache Spark machine learning blueprints
par: Liu, Alex.
Publié: (2016)

Apache Spark 2.x cookbook
par: Yadav, Rishi.
Publié: (2017)

Apache Spark 2 : master complex big data processing, stream analytics, and machine learning with Apache Spark
Publié: (2018)

Apache Spark graph processing
par: Ramamonjison, Rindra.
Publié: (2015)

Apache Spark quick start guide : quickly learn the art of writing efficient big data applications with Apache Spark
par: Mehrotra, Shrey.
Publié: (2019)

PySpark cookbook : over 60 recipes for implementing big data processing and analytics using Apache Spark and Python
par: Lee, Denny.
Publié: (2018)

Keras deep learning cookbook : over 30 recipes for implementing deep neural networks in Python
par: Dua, Rajdeep.
Publié: (2018)

Apache Spark 2.x for Java developers
par: Gulati, Sourav.
Publié: (2017)

Machine learning with Apache Spark quick start guide : uncover patterns, derive actionable insights, and learn from big data using MLlib
par: Quddus, Jillur.
Publié: (2018)

Mastering Apache Spark 2.x : scalable analytics faster than ever
par: Kienzler, Romeo.
Publié: (2017)

Practical Machine Learning with Spark : Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML
par: Gupta, Gourav.

Databricks Certified Associate Developer for Apache Spark Using Python : The ultimate guide to getting certified in Apache Spark using practical examples with Python
par: Shah, Saba.

Python deep learning cookbook
par: Bakker, Indra Den.
Publié: (2017)

Frank Kane's taming big data with Apache Spark and Python
par: Kane, Frank.
Publié: (2017)

Spark Cookbook
par: Yadav, Rishi.
Publié: (2015)

Machine learning with Spark
par: Dua, Rajdeep.
Publié: (2017)

Learning PySpark
par: Drabas, Tomasz.
Publié: (2017)

Learning Spark SQL
par: Sarkar, Aurobindo.
Publié: (2017)

Learning Apache Thrift
par: Rakowski, Krzysztof.
Publié: (2015)

Learning Apache Cassandra
par: Brown, Mat.
Publié: (2015)

Learning Apache Apex
par: Weise, Thomas (19..-....).
Publié: (2017)

Learning Apache Cassandra
par: Yarabarla, Sandeep.
Publié: (2017)

Learning Apache Mahout
par: Tiwary, Chandramani.
Publié: (2015)

Deep Learning with R Cookbook : Over 45 unique recipes to delve into neural network techniques using R 3.5.x
par: Gupta, Swarna.
Publié: (2020)

Apache Camel developer's cookbook : solve common integration tasks with over 100 easily accessible Apache Camel recipes
par: Cranton, Scott.
Publié: (2013)

Deep Learning with MXNet Cookbook : Discover an extensive collection of recipes for creating and implementing AI models on MXNet
par: Torres, Andrés P..

Deep learning
par: Kelleher, John D. (1974-....).
Publié: (2019)

Apache Karaf cookbook
par: Nierbeck, Achim.
Publié: (2014)

Apache Maven cookbook
par: Bharathan, Raghuram.
Publié: (2015)

Apache Mesos cookbook
par: Blomquist, Donald S..
Publié: (2017)

Apache Hive cookbook
par: Bansal, Hanish.
Publié: (2016)

Deep learning by example : a hands-on guide to implementing advanced machine learning algorithms and neural networks
par: Menshawy, Ahmed.
Publié: (2018)

Deep learning with Hadoop : build, implement and scale distributed deep learning models for large-scale datasets
par: Dev, Dipayan.
Publié: (2017)

Deep Learning for Time Series Cookbook : Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
par: Cerqueira, Vitor.

TensorFlow 1.x Deep Learning Cookbook
par: Gulli, Antonio.
Publié: (2017)

Java Deep Learning Cookbook : Train neural networks for classiﬁcation, NLP, and reinforcement learning using Deeplearning4j
par: Raj, Rahul.
Publié: (2019)

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1