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

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

Salvato in:

Dettagli Bibliografici
Autore principale:	Gupta, Gourav. (Autore)
Altri autori:	Gupta, Manish (19..-....; informaticien). (Auteur), Singh Gupta, Inder.
Natura:	E-Book
Lingua:	Anglais
Pubblicazione:	New Delhi : BPB Publications.
Autres localisations:	Voir dans le Sudoc
Accesso online:	Accès à l'E-book

Documenti analoghi

Apache Spark machine learning blueprints
di: Liu, Alex.
Pubblicazione: (2016)

Machine learning with Spark
di: Dua, Rajdeep.
Pubblicazione: (2017)

Apache Spark 2.x machine learning cookbook
di: Amirghodsi, Siamak.
Pubblicazione: (2017)

Learning Apache Spark 2
di: Abbasi, Muhammad Asif.
Pubblicazione: (2017)

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

Machine learning with Spark and Python : essential techniques for predictive analytics
di: Bowles, Michael (19..-....).

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

Mastering machine learning with Spark 2.x
di: Tellez, Alex.
Pubblicazione: (2017)

Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark
di: Sherif, Ahmed.
Pubblicazione: (2018)

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

Learning Spark SQL
di: Sarkar, Aurobindo.
Pubblicazione: (2017)

Learning PySpark
di: Drabas, Tomasz.
Pubblicazione: (2017)

Spark : valorisez vos données en temps réel avec Spark ML et Hadoop
di: Jouin, Romain.
Pubblicazione: (2020)

Apache Spark graph processing
di: Ramamonjison, Rindra.
Pubblicazione: (2015)

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

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

Apache Spark 2.x cookbook
di: Yadav, Rishi.
Pubblicazione: (2017)

Mastering Machine Learning on AWS : advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
di: Mengle, Saket S.r..
Pubblicazione: (2019)

Practical Machine Learning on Databricks : Seamlessly transition ML models and MLOps on Databricks
di: Sinha, Debu.

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

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

Apache Spark 2.x for Java developers
di: Gulati, Sourav.
Pubblicazione: (2017)

Spark Cookbook
di: Yadav, Rishi.
Pubblicazione: (2015)

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

Practical Machine Learning
di: Gollapudi, Sunila.
Pubblicazione: (2016)

Microservices for Machine Learning : Design, implement, and manage high-performance ML systems with microservices
di: Ranjan, Rohit.

Hands-on data science and Python machine learning : perform data mining and machine learning efficiently using Python and Spark
di: Kane, Frank.
Pubblicazione: (2017)

Spark : The Life of Electricity and the Electricity of Life
di: Jorgensen, Timothy J..
Pubblicazione: (2021)

Spark for Data Science
di: Duvvuri, Srinivas.
Pubblicazione: (2016)

Syntony and Spark : The Origins of Radio
di: Aitken, Hugh G.J..
Pubblicazione: (2014)

The machine learning workshop : get ready to develop your own high-performance machine learning algorithms with scikit-learn
di: Saleh, Hyatt.
Pubblicazione: (2020)

Practical machine learning in R
di: Nwanganga, Fred (19..-....).

Practical Machine Learning Cookbook
di: Tripathi, Atul.
Pubblicazione: (2017)

Essential PySpark for Scalable Data Analytics : A beginner's guide to harnessing the power and ease of PySpark 3
di: Nudurupati, Sreeram.
Pubblicazione: (2021)

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

Practical Full Stack Machine Learning : A Guide to Build Reliable, Reusable, and Production-Ready Full Stack ML Solutions
di: Kumar, Alok.

Hands-On Machine Learning with ML.NET : Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
di: Capellman, Jarred.
Pubblicazione: (2020)

Computer and machine vision : theory, algorithms, practicalities
di: Davies, E. Roy (1948-....).
Pubblicazione: (2012)

Mastering Spark for data science
di: Morgan, Andrew.
Pubblicazione: (2017)

Practical Mathematics for AI and Deep Learning : A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning (English Edition)
di: Ghosh, Tamoghna.

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