About This Activity
I read in turn with my friends using Translated one. Translated one is divided into two books. We are going to read Volume 2 this spring vacation(2019).
We read Volume 1 last summer. Here is a link to that.
Last summer my motivation is “to know exactly what AI can do and cannot do”, but it has little changed. I also want to know mathematics under the application of models. Through the class at at the college, I learnt some models and some applications of big data. Some algorithms in the machine learning field are useful in other field, like clustering, Markov model and so on. Thorough this book, I want to master the better application of data and mathematics that can be useful in modeling.
I read this book with friends from a lot of backgrounds.
They are from economics, bioinformatics, computer science, physics and mathematics. Fortunately, we could invite graduated students this spring!!
I made some notebooks for each chapters so that OI can remember what I did in this book.
Chapter 6: Kernel Methods
Chapter 7: Sparse Kernel Machines
Chapter 8: Graphical Methods
Chapter 9: Mixture Models and EM
Chapter 10: Approximate Inference
Chapter 11: Sampling Methods
Chapter 12: Continuous Latent Variables
Chapter 13: Sequential Data
Chapter 14: Combining Models