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Machine Learning - A Comprehensive, Step-by-Step Guide to Intermediate Concepts and Techniques in Machine Learning

Machine Learning - A Comprehensive, Step-by-Step Guide to Intermediate Concepts and Techniques in Machine Learning

by Peter Bradley
Paperback
Publication Date: 24/06/2019

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Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place.



This book is a sequel to the book titled 'Machine Learning: A Step-by-Step guide.' In the first book, you gathered information on what machine learning is, and the different algorithms that one needs to know. This book is written for those who have a basic understanding of what machine learning is.



In this book, you will gather information on:



Practical examples of machine learning
How to build a machine learning algorithm in Python
An introduction to deep learning and neural networks
How to create a neural network in Python using Keras
And much more



The book breaks the process of building a machine-learning model in Python into simple steps. These steps will help you build your very own machine-learning model from scratch. You should first build the model using the programs and scripts given in the book before you build your model from scratch. If you want to learn more about what you can do with machine learning, then this is the perfect book for you.



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ISBN:
9781393462446
9781393462446
Category:
Uncategorized
Format:
Paperback
Publication Date:
24-06-2019
Publisher:
Draft 2 digital
Pages:
96
Dimensions (mm):
216x140x6mm
Weight:
0.13kg
Peter Bradley

Peter Bradley was the Labour MP for The Wrekin between 1997 and 2005. More recently, he co-founded and directed Speakers' Corner Trust, a charity which promotes freedom of expression, open debate and active citizenship in the UK and developing democracies. He has written, usually on politics, for a wide range of publications, including The Times, The Guardian, The Independent, The New Statesman and The New European.

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