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, by Samuel Burns
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Product details
File Size: 3979 KB
Print Length: 148 pages
Page Numbers Source ISBN: 1731394160
Publication Date: November 8, 2018
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07KCDNKM1
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Amazon Best Sellers Rank:
#209,012 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
I found this book to be very clearly written and also very informative since in addition to providing code examples it tried to illustrate the basics of theory behind what makes machine learning work.The explanations were mainly done by showing examples of data on a x-y plot and how the different techniques separate the data to make a decision. This is a nice way to reduce the complexity of explanation and getting lost in the details of the mathematics and programming syntax etc and to get at the heart of where different algorithms have strengths.This is review is from the perspective of someone who knows a little python and had little knowledge of machine learning, but has kind of seen neural nets and regressions used in different applications over the years.Part of its usefulness to me is that it gives me a nice way to explain machine learning to non-scientists.
I bought this book to follow along with. it starts talking about a file in a directory student_marks.csv - without ever mentioning any download anywhere.I have search back and forth in the first 39 pages (where it starts assuming we have this file) and cannon find any reference to a download. Can't follow along without the data :(
This is a great book for software engineers who want to know more about machine learning. I took the python class on Udemy which was a great introduction to ML. I was looking for something simple to start the ML . I found this Samuel Burn’s book with more details that covers all different algorithms. This book is exactly what i wanted. My python knowledge is also just basic and I haven't struggled at all.
I find this book very informative, helpful and interesting for all the people who want to know about Python Machine Learning. I like how the book is written in a very well explained way. The author makes sure that the readers can understand every details of this book. Thanks to Samuel Burns for this great book. I found many useful things inside the book.Overall, the book is very informative and worthy of attention!
Python Machine Learning book is really a creative one for me.I am so much excited to do something great by the help of the book suggestion.This book contains something hidden secret formulas that is very informative for learning python learning.
This is a book for those who want to understand machine learning algorithm, and then try out the algorithm using Scikit-Learn or TensorFlow. Minimal mathematics formulas are used, which is good, as I prefer the explanation of the idea, instead of decoding the method. I recommend this book for everyone. It seems cheaper but excellent.
The content was very clear. I have not found a better explanation of Deep Learning concepts along with accompanying TensorFlow implementation. Great job by author to keep it so simple and yet covering the concepts exhaustively. I highly recommend it.
Easy to read and well written! This guide explained almost everything you need to know about Python Machine Learning. Through this book, I learned this programming language in a easier and step by step approach. Overall, it was great read!
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