Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn

BOOKS - Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas ...

Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn - Abdelaziz Testas 2023 PDF | EPUB | MOBI Apress BOOKS

ECO~19 kg CO²

2 TON

13871

Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn

Author: Abdelaziz Testas
Year: 2023
Pages: 500
Format: PDF | EPUB | MOBI
File size: 10.1 MB
Language: ENG

Pay with Telegram STARS

Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and ScikitLearn In today's fast-paced world, technology is constantly evolving at an unprecedented rate, and it is essential to stay up-to-date with the latest advancements in the field of machine learning. One such technology that has gained significant attention in recent years is distributed machine learning, which enables the training of complex models on large datasets using multiple machines or nodes. This technology has revolutionized the way we approach data analysis and modeling, making it possible to handle massive amounts of data and perform complex computations with ease. However, transitioning from traditional machine learning libraries like pandas and scikit-learn to distributed machine learning can be challenging, especially for those who are new to the field. This book, "Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and ScikitLearn," aims to provide a comprehensive guide to help readers migrate seamlessly from traditional machine learning libraries to distributed machine learning using PySpark. The book covers various aspects of distributed machine learning, including the basics of distributed computing, the benefits of distributed machine learning, and the process of migrating from traditional machine learning libraries to PySpark.

You may also be interested in:

Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn

Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)

Distributed Machine Learning Patterns (MEAP v7)

Robust Machine Learning Distributed Methods for Safe AI

Distributed Machine Learning Patterns (Final Release)

Scaling Up Machine Learning Parallel and Distributed Approaches

Distributed Artificial Intelligence for 5G/6G Communications Frameworks with Machine Learning

Simple Machine Learning for Programmers Beginner|s Intro to Using Machine Learning, Deep Learning, and Artificial Intelligence for Practical Applications

Machine Learning for Beginners A Complete and Phased Beginner’s Guide to Learning and Understanding Machine Learning and Artificial Intelligence Algoritms

Ultimate Parallel and Distributed Computing with Julia For Data Science Excel in Data Analysis, Statistical Modeling and Machine Learning by Leveraging MLBase.jl and MLJ.jl to Optimize Workflows

Python Machine Learning The Ultimate Guide for Beginners to Machine Learning with Python, Programming and Deep Learning, Artificial Intelligence, Neural Networks, and Data Science

Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models

Essential PySpark for Scalable Data Analytics: A beginner|s guide to harnessing the power and ease of PySpark 3

Machine Learning for Beginners An Introductory Guide to Learn and Understand Artificial Intelligence, Neural Networks and Machine Learning

Machine Learning in Production: Master the art of delivering robust Machine Learning solutions with MLOps (English Edition)

Building Machine Learning Systems Using Python Practice to Train Predictive Models and Analyze Machine Learning Results

Machine Learning for Business The Ultimate Artificial Intelligence & Machine Learning for Managers, Team Leaders and Entrepreneurs

Serverless Machine Learning with Amazon Redshift ML: Create, train, and deploy machine learning models using familiar SQL commands

Applied Machine Learning and High-Performance Computing on AWS: Accelerate the development of machine learning applications following architectural best practices

Online Machine Learning: A Practical Guide with Examples in Python (Machine Learning: Foundations, Methodologies, and Applications)

Machine Learning Master Machine Learning Fundamentals for Beginners, Business Leaders and Aspiring Data Scientists

Machine Learning for Data Streams with Practical Examples in MOA (Adaptive Computation and Machine Learning series)

Machine Learning The Ultimate Guide to Understand AI Big Data Analytics and the Machine Learning’s Building Block Application in Modern Life

Machine Learning for Beginners Build and deploy Machine Learning systems using Python, 2nd Edition

Machine Learning: A Guide to PyTorch, TensorFlow, and Scikit-Learn: Mastering Machine Learning With Python

Machine Learning with Core ML 2 and Swift A beginner-friendly guide to integrating machine learning into your apps

Programming Machine Learning Machine Learning Basics Concepts + Artificial Intelligence + Python Programming + Python Machine Learning

Programming With Python 4 Manuscripts - Deep Learning With Keras, Convolutional Neural Networks In Python, Python Machine Learning, Machine Learning With Tensorflow

Computer Programming This Book Includes Machine Learning for Beginners, Machine Learning with Python, Deep Learning with Python, Python for Data Analysis

Machine Learning, Animated (Chapman and Hall CRC Machine Learning and Pattern Recognition)

Machine Learning for Finance Master Financial Strategies with Python-Powered Machine Learning

Machine Learning for Beginners A Practical Guide to Understanding and Applying Machine Learning Concepts