732A99-Notes

• Main Blog
• Notes and R-code implementation for various topics covered in 732A99 Machine Learning course offered at Linköping University.
• R was the language of choice for this course and sometimes I really struggled to implement certain concepts. This repo is an ateempt to record some if's and but's to keep in mind while programmingin R. Hope this helps!
• Primary source of reference was Bishop's Pattern Recognition and Machine Learning. All the equations quoted within code snippets or notes can be found in this book.
• Secondary source of reference was The Elements of Statistical Learning (ESL)

Other Helpful Resources

• PRML R Implementation : João Neto's R codes are great. Do check them out.
• ISLR 2nd-Edition : 2nd Edition came out recently. Also deals with topics such as Multiple Testing and Neural Networks. Everything is in R-language.
• Applied Predictive Modeling : Covers important ML ALgo's and their R-implementation.

NOTE: In case I have missed to give proper attribution and reference, please raise an issue and I shall correct it.