## Resources-For-ML

Here is a curated List of Resources for Machine Learning

### A. Machine Learning

1) My personal favourite, I started my datascience journey with this and I recommend it as a starting point,not too heavy on the math though Data-mining Concept and Techniques

2) Complement the above with this to ease into the math A comprehensive overview of ML, with a lot of technicalities explained: Machine Learning by Tom Mitchell

### B. Getting into the mathematics:

#### Probability

- 1A) I believe this is a far better book for a beginner in probability than the one that follows Pattern Recognition and Machine Learning, Christopher Bishop
- 1B) Read on the mathematical foundations bit,just basics, the math is still too difficult to comprehend for a beginner by my guesstimate Pattern Classification - Duda, Hart

You may start either with 1A / 1B, I strongly recommend 1A + 2A/2B to get a hold on probability

- 2A) Follow quickly with Bayesian Reasoning And Machine Learning
- 2B) Probability bits from All of Statistics: A Concise course in statistical inference by Larry Wasserman
- 3A) Supplement with the following to dvelve into scary math territory Ian Goodfellow book on Deep learning

#### Statistics

- 1) Start with this and no other All of Statistics: A Concise course in statistical inference by Larry Wasserman
- 2) Easy Stats and implemented in python Think stats
- 3) Statistics with R by Andy Field
**Especially to Learn R** - 4) Just to Complement above readings you may try outIntro to bayesian statistics by William Bolstad
- 5) Finish with this. It is has by far the most challenging and detailed explanationsThe Elements of Statistical Learning: Data Mining, Inference and Prediction

#### Information theory

Information Theory, Inference and Learning Algorithms by David J.C. MacKay

#### Linear Algebra

- 1) One by 3Blue1Brown Linear Algebra
- 2) Linear algebra bits from this book Ian Goodfellow book on Deep learning
- 3) Try out for
**solving sums**Introduction to Linear Algebra By Gilbert Strang

More to comeā¦.

### C. Visual Resources

Nothing better than the 3Blue1Brown