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Python Machine Learning   

Python Machine Learning


Samuel Hack

Hardback. Samuel Hack 2021-03-03.
ISBN 9781801728539
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55% OFF for Bookstores for the next 3 days only! Do you want to understand machine learning, but it all looks too daunting and complex? Afraid to open the 'pandora's box' and waste hours searching for answers? Your customers will have no more secrets about the future development of artificial intelligence! Written with the beginner in mind, this powerful guide breaks down everything you need to know about machine learning and Python in a simple, easy-to-understand way. So many other books make machine learning look impossible to understand and even harder to master - but now you can familiarize yourself with this incredible technology like never before! With a detailed and concise overview of the fundamentals, along with the challenges and limitations currently being tackled by the pros, inside this comprehensive guide, you will: Learn the Fundamentals of Machine Learning which Are Being Developed and Advanced with PythonMaster the Nuances of 12 of the Most Popular and Widely-Used Machine Learning Algorithms, in a Language that Requires No Prior Background in PythonDiscover the Details of the Supervised, Unsupervised, and Reinforcement Algorithms, which Serve as the Skeleton of Hundreds of Machine Learning Algorithms Being Developed Every DayBecome Familiar with Data Science Technology, an Umbrella Term Used for the Cutting-Edge Technologies of TodayDive Into the Functioning of Scikit-Learn Library and Develop Machine Learning Models, with a Detailed Walkthrough and Open Source Database using Illustrations and actual Python CodeUnderstand the Entire Process of Creating Neural Network Models on TensorFlow, Using Open Source Data Sets and real Python CodeUncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets With a wealth of tips and tricks, along with invaluable advice



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Python Machine Learning
Python Machine Learning
  
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