Machine Learning Engineering Book

164 16 6 years ago

manojlds2• 6 years ago

Says read first and but later but don't see any option to download without paying?

swyx• 6 years ago

did you even click the links? they link each chapter to dropbox https://www.dropbox.com/s/wxybbtbiv64yf0j/Chapter1.pdf?dl=0

kgwgk• 6 years ago

It’s unclear from the page if these chapters are the final version.

franczesko• 6 years ago

How this book is different from the "The Hundred-Page Machine Learning Book" or "Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems"?

st1x72• 6 years ago

The main difference is that "Hands-On ML..." is a legitimately good book.

sgt1012• 6 years ago

I think that it's unfair of you just to assert this without giving some specific criticism of this book.

I am pretty interested actually as I am currently trying to write a similar book of my own! I can see a lot of difference between this and what I am trying to do, and may differences to "Hands on" but what in particular are you disappointed with here?

dhanainme• 6 years ago

"The Hundred-Page Machine Learning Book" will teach you what ML is. It can be a treated as a light weight replacement for say an Andrew NG course. You wont learn anything practical / code something in PyTorch or Tensorflow but you ll understand what happens under the hood in these framework

"Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" is an amazing introduction to implementing all ML ideas. I think there is a new PyTorch version. The accompanying notebook will get you started to a point where you can do some hobby projects.

This book surprisingly seems to fill an interesting gap explaining about how these ML systems are used in real life in large scale. I work for 1 of the FAANG companies & I can say that every chapter here would correspond to bread & butter of a team responsible for maintaining a large ML system say Recommendation / Fraud detection. The target audience would be someone who is interested to learn how to put a large end-end ML system together.

I would be very excited if there are practical examples on how to use this with MLFlow / KubeFlow / Sagemaker. Really excited to read this

edit : typos

desku• 6 years ago

Is there actually a new PyTorch version? I can't seem to find anything about it online.

danielscrubs• 6 years ago

The information in that book will age like milk, while the hundred page book will age like wine.

goku99• 6 years ago

Thanks a lot for this! It's really helpful

Machine Learning Engineering Book

Related Stories