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, by Samuel Burns
Download , by Samuel Burns
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Product details
File Size: 3984 KB
Print Length: 148 pages
Publication Date: March 12, 2019
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07PQNQJ58
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Amazon Best Sellers Rank:
#77,914 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
This book shows some excellent uses of scikit learn. Intermediate python user level.Easy bookWell Written By Author.Good step by step writing .
Very accessible and very cheap book for a beginner.
This book is a tour of Machine Learning with Python, using the most popular libraries. The book is easy and intuitive for a beginner. I would recommend all absolute beginner to start machine learning from this book. It is a nice introduction to Machine Learning without much maths needed. This book will give you a good sense of the basics, a walkthrough of scikit-learn and hopefully some intuition about the popular algorithms. This book is very useful for every practitioner who wants to apply a machine learning algorithm to real world problems because of example codes in the book. I am very happy that I bought this book.
Best book on Machine Learning ever! I recommend it for beginners.
This book could be extremely helpful if you are a beginner in machine learning fundamentals in general, and machine learning using python in particular. Of course, some basic prior programming experience is a must, but overall it's a very detailed book that I highly recommend
This is a great book for software engineers who want to learn machine learning. I was looking for something with more details that covers all different algorithms. This book is exactly what I need. Thank you!
I'm very pleased with this book. It includes complete practical approach to machine learning topic. Not only details about all algorithms, but also discusses various critical steps in preparing the data sets for ML work, evaluating the models using APIs from Scikit-Learn and Tensor Flow.Can't wait to attempt two RNN projects at the end of the book.
I am a generally new at python, and have never been related with a portion of the libraries in the book. The coding was immediatly over my head yet was realatively simple to make sense of. Simply going throught the coding and examining what was happening has shown me a lot about python and the AI/math libraries. In the event that you really need to learn, and are not hesitant to put in some additional homework, I exceptionally recommend this book.
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