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Resources for Machine Learning Systems: Designs that scale

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I worked on developing the materials for Machine Learning Systems over quite a while, in a number of different formats. My personal site, jeffsmith.tech brings a lot of those together.

Breaking it down in a bit more detail, here's a guided tour of places you can dive in:

All of the code in the book can be found on the GitHub repo. I have some minor updates to post there, so star that repo if you want to get the latest.

I concurrently developed all of the code examples in the book as conference and meetup talks as well. This gave me the ability to work out some of the bugs in my ideas and get direct, realtime feedback from audience members. You can find a listing of these talks on the speaking section of my site. Since many of these talks were recorded, you can use these videos to mix up the modality of your studying and hear a bit more from me about the real world context of some of these techniques.

I've also done a few interviews that touch on the materials in the book. In particular, this written interview with Manning and this podcast interview with Defrag This.

I also sporadically blog on Medium and will probably be posting more supplementary thoughts in support of the book.

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