Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
What if you could ensure a shared moment of clarity after you or your life partner have succumbed to dementia? Would you plant a seed to be able to trigger that moment later in life?
My Spark AR Studio Development Tests – Part 1.
I need to do some more general updates. I'm failing at the goal of this whole blog, which is really to just write. I'm a guilty of making things too...
I generally laugh when I see the media and most people saying that Amazon and Google are listening to you when you don't know it. It's simply not true. I...
Next time you think about complaining about a Microsoft update and how they make such awful things that you use on a daily basis, take the following into consideration. Think...
This is an amazing set of Kubernetes learning materials and tutorials from Microsoft, published in 2018. It's full of videos and a minor amount of reading. You can probably blow...
https://github.com/abhat222/Data-Science--Cheat-Sheet If there's anything we could use every now and then it's a good cheat sheet. After years of programming there are so many things you learn with every new...
This is a great site for learning about how companies are using different Amazon Web Services to accomplish their application goals. It's all about architecture and getting ideas for different...
I started working on what will become either a game, or a coffee table book about passive aggressive things you can do at work to make yourself feel better about...
