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Advanced Machine Learning with Python Paperback – July 28, 2016
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About the Author
John Hearty is a consultant in digital industries with substantial expertise in data science and infrastructure engineering. Having started out in mobile gaming, he was drawn to the challenge of AAA console analytics. Keen to start putting advanced machine learning techniques into practice, he signed on with Microsoft to develop player modelling capabilities and big data infrastructure at an Xbox studio. His team made significant strides in engineering and data science that were replicated across Microsoft Studios. Some of the more rewarding initiatives he led included player skill modelling in asymmetrical games, and the creation of player segmentation models for individualized game experiences. Eventually John struck out on his own as a consultant offering comprehensive infrastructure and analytics solutions for international client teams seeking new insights or data-driven capabilities. His favourite current engagement involves creating predictive models and quantifying the importance of user connections for a popular social network. After years spent working with data, John is largely unable to stop asking questions. In his own time, he routinely builds ML solutions in Python to fulfil a broad set of personal interests. These include a novel variant on the StyleNet computational creativity algorithm and solutions for algo-trading and geolocation-based recommendation. He currently lives in the UK.
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Top customer reviews
I am a Analyst, I have a MSc. in Mathematics and Statistics and do analytics for a living. While I have studied about neural networks and machine learning a while ago, only past year have I (re)-discovered the power of neural nets and Deep Learning.
In my quest to improve my knowledge, I have taken many certificates in ML and have bought a few books about Machine Learning. Among these are:
-Python Machine Learning by Sebastian Raschka (recommended)
-Building Machine Learning Systems with Python by by Luis Pedro Coelho and Willi Richert (nice to have for additional perspective)
However, I wanted to go beyond what one can find in those two books. The topics I was specifically interested in were:
-Deep Belief Networks (inc. Restricted Boltzmann Machine)
-Convolutional Neural Networks
So where does Advanced Machine Learning rank among these?
I must say, and that will be my main criticism of the book that it is not for the faint of heart. It is fast, sometimes too fast... I suppose there is so much you can put in 250 pages to explain about these topics, and it is easy to become lost.
However, do not get me wrong. This book is a small gem in itself.
Why? Because while I have found online many tutorials or courses about the topics I was interested, the book gives you additional information and explanations that I haven't found anywhere else. How do you set your hyper-parameters in a CNN? What is the depth exactly representing, what are the current architectures, are they really all that good? Why?
It is the difference between the how and the more precise what and why. Tutorials online are great but many people just do things without clearly showing why. This books gives you the clues.
In conclusion, for me currently (after having bought 8 books):
The book is difficult but not super difficult. It gives more understanding and depth than I could ever obtain with all the material available online currently (including the very good Stanford courses). So, yes, I feel I am making progress.
-Python Machine Learning by Sebastian Raschka is the way to go for Machine Learning foundations
-Advanced Machine Learning with Python by John Hearty is a super helpful complement to what one can already find online dispersed all over the place, it just make sense with better hindsight.
With so many errors in *the very first code sample*, I'm setting this book down and stepping slowly away. I don't know if what this book is trying to teach me is even correct, much less useful. Perhaps the authors should learn basic coding and editing skills before, you know, machine learning?