It is a blueprint to data science from the mathematics to algorithms. It is not completed. It is of my own interest. It is web-source based. And some material draw from the original owners' blogs. Last but not least, thanks to the teachers who guide me to mathematics. And the copyright of pictures are not permmited by the original oweners. If this material infringes your copyright, you could contact me via Github and I will delete the pictures.

I hope that it is on the ADEPT way like Kalid Azad

It is expected a part of A Guide to Data Science.

It includes the architure, optimization method and regularization, acceleration and compression.

It includes the following content:

• basic introduction to probability and statistics;
• sampling algorithm based on uniformly distributed data;
• MCMC and stochastic methods;
• generalized linear model and regression analysis;
• basic machine learning;
• some materials on artifical neural network and deep learning;
• probabilistic programming and graph models;
• other data anslysis such as topological data analysis;
• other computational intelligence such as simulated annealing.