Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas an

Description: Distributed Machine Learning with PySpark by Abdelaziz Testas Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Migrate from pandas and scikit-learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools.Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Naïve Bayes, and neural networks.After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary toapply these methods using PySpark, the industry standard for building scalable ML data pipelines.What You Will LearnMaster the fundamentals of supervised learning, unsupervised learning, NLP, and recommender systemsUnderstand the differences between PySpark, scikit-learn, and pandasPerform linear regression, logistic regression, and decision tree regression with pandas, scikit-learn, and PySparkDistinguish between the pipelines of PySpark and scikit-learn Who This Book Is ForData scientists, data engineers, and machine learning practitioners who have some familiarity with Python, but who are new to distributed machine learning and the PySpark framework. Author Biography Abdelaziz Testas, Ph.D., is a data scientist with over a decade of experience in data analysis and machine learning, specializing in the use of standard Python libraries and Spark distributed computing. He holds a Ph.D. in Economics from Leeds University and a Masters degree in Finance from Glasgow University. He has also earned several certificates in computer science and data science.In the last ten years, he has worked for Nielsen in Fremont, California as a Lead Data Scientist focused on improving the companys audience measurement through planning, initiating, and executing end-to-end data science projects and methodology work. He has created advanced solutions for Nielsens digital ad and content rating products by leveraging subject matter expertise in media measurement and data science. He is passionate about helping others improve their machine learning skills and workflows, and is excited to share his knowledge and experience with a wider audience through this book. Details ISBN 1484297504 ISBN-13 9781484297506 Title Distributed Machine Learning with PySpark Author Abdelaziz Testas Format Paperback Year 2023 Pages 490 Edition 1st Publisher APress GE_Item_ID:157396743; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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