Preview
  • Machine Learning: A Two-Book Bundle

  • Machine Learning and Agile Project Management
  • By: Robert Keane
  • Narrated by: Mike Davis
  • Length: 2 hrs and 53 mins
  • 4.7 out of 5 stars (16 ratings)

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Machine Learning: A Two-Book Bundle

By: Robert Keane
Narrated by: Mike Davis
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Publisher's summary

This audiobook includes two manuscripts.

Machine Learning: Master the Three Types of Machine Learning

Machine learning is vital to the world of information technology. While many people may have no idea what machine learning is, they have probably used it sometime in their daily lives. For example, if you have ever done a search query on a search engine, you have worked with one form of machine learning. The program to do your search query has been trained to find the best results based on what you are looking for, and it will also learn from the choices that you make.

Agile Project Management: Focus on Continuous Improvement, Scope Flexibility, Team Input, and Delivering Essential Quality Products

Agile project management has grown in popularity over the past several years. Change is occurring so fast that many organizations are unable to keep up with the demands of a changing global world. Your ability to quickly change and adapt to your environment will make or break not only your career, but could be the deciding factor as to whether your company survives in the coming years. Those that have implemented the agile strategies you will learn in this audiobook are the ones that are succeeding and will be around for years to come.

©2017 Robert Keane (P)2017 Robert Keane
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What listeners say about Machine Learning: A Two-Book Bundle

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theoratical knowwledge

Out of many different machine learning books that I have tried this one is by far the best one. Highly recommended, especially if you already have some basic theoretical knowledge

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recommende to all

Basic but we'll presented. As it says "for the beginners". But a worth taking your time starting point. Recommended to all

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solid intro

Great book for anyone wanting to get a general understanding of machine Learning.

Book provided great examples and points one in the right direction for future learning.

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great overview

This is a fantastic book for the absolute beginner. Although extremely elementary in content, it is very useful for someone with no background

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awesome

This book is really an exceptional guide and reference if you're at the knee in the learning curve. You've dabbled a bit with machine learning, have heard the basic concepts, know what Kaggle is, have read a bit about the fundamentals from Wikipedia and on-line guides and have wetted your appetite to get some hands-on experience. That's where I was and I found myself just getting lost when listening Goodfellow. I'm about half way though and haven't found the urge to skip over anything yet. Also its the first technical book I've been able to follow on a kindle paper white. The way it walks you through is really artful.

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thank you

Touches all important terminology and explanations are simple so even a firmware engineer like me could follow easily. Easy . I could finish it in two flights. Now time to practise. Thank you.

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fresh my head


As a standalone book it won’t be enough to train yourself to become a machine learning engineer – although it does include a chapter on job & study options – so it really should be used as an entry point to ML and not a comprehensive guide. To be honest, I’d still be CLUELESS if I went to my CLI today and wanted to start a machine learning model. But for a few bucks this book has done its job and I feel much more confident tackling other introductory resources to Scikit Learn and Tensorflow now that I have all the basic principles and terminology fresh in my head

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great intro

Excellent introduction to ML and easy to listen in just a couple hours or so. No math or stats or system knowledge required for this level of awareness

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great book for beginners

This is a great book for software engineers who want to know more about machine learning. I took the machine learning class on Coursera which was a great introduction in matlab to ML. I was looking for something with more details that covers all different algorithms. This book is exactly that. My python knowledge is also just basic and I haven't struggled at all

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suggested

Short, simple and easy listten
I would recommend beginners in the subject to have this book first before taking any classes

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