Ebook , by Daniel Vance
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, by Daniel Vance
Ebook , by Daniel Vance
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Starting to read this book can start your chance in doing this life better. It will certainly make you look to have even more times or more leisures in analysis. Reserving few times in a day just for reading can be done as one of the initiatives for you to finish your tasks. When you will finish the evening prior to sleeping, , By Daniel Vance is likewise an advantage to accompany you.
Product details
File Size: 9182 KB
Print Length: 119 pages
Simultaneous Device Usage: Unlimited
Publisher: AI Sciences; 1 edition (February 8, 2019)
Publication Date: February 8, 2019
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07NKDDX7R
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Amazon Best Sellers Rank:
#16,138 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
Very interesting book if your are a beginner in the Machine Learning and looking for a small and quick book to practice ML in Python.This book is really an beginner guide and reference if you're at the beginning level in the learning curve. You've dabbled a bit with machine learning, have heard the basic concepts, know what Linear regression and decision tree are, have read a bit about the fundamentals from Wikipedia and online and have wetted your appetite to get more about Machine Learning . That is where I was and I found myself just getting lost when reading an academic books. Therefore, I found this book and it is a very complete beginner book in Python Machine Learning.I also purchased the book “Machine Learning essentialsâ€. Thanks the author now I think I master all the concepts and know how to apply some of them on Python!!! I am very happy
The information provided is a fantastic introduction to Python machine learning. It is like a tutorial where all the important elements are explained clearly.I felt like there was always some knowledge assumed about ordinary machine learning that I was lacking. What is the difference between the machine learning algorithm and where to apply each of them! Now I understand well where each algorithm is applied and how to run all these algorithms in Notebook Jupyter. The codes is available online and very nicely organised.
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