Since I am a massive believer of free education, below I’ve compiled a list of some of my favorite study materials, research papers, lectures etc. These could be of interest if you are into particle physics/astrophysics/machine learning. They are all free!

A more generic and extremely useful list of such free materials for theoretical physicists has already been prepared by famous physics professor *Gerard ‘t Hooft*. You can check the site: How to Become a Good Theoretical Physicist.

Below goes my list:

*Particle Physics*:

*Standard Model*:

- Introduction to Standard Model.
- Getting Started with Noether’s Theorem. First 3 chapters are really helpful.
- Feynman Diagrams for Beginners. Also, Griffiths Particle Physics Book, Appendix D.
- Complete Lecture Series of Particle Physics: Lenny Susskind.
*My Favorite teacher!*

*Dark Matter*:

- Lectures on Dark Matter. Also check for other TASI Lecture Notes.
- Fantastic Compilation of Lecture Notes on Dark Matter

*Astrophysics; Cosmology and Cosmic Rays* :

*Cosmology Basic to Intermediate to Advanced*:

- Lectures notes on Cosmology.
- Lecture notes on Cosmology. Contains a very intuitive explanations of rather difficult topics.
- Lecture notes on General Relativity. A very comprehensive guide.
- Understanding CMB Power Spectrum.
- CMB Power Spectrum for Pedestrians.

*Dark Matter Indirect Detection*:

- Review of Indirect Searches of Particle Dark Matter.
- DM Candidates from Particle Physics and Detection Methods.
- $\gamma$ rays and Dark Matter Review.

*Cosmic Rays*:

- Origin of Galactic CRs: P.Blasi.
- Cosmic-Ray Transport: E.Amato.
- Cosmic-Ray Lecture Notes: M. Kachelriess.
- Cosmic-Ray Models: M.Kachelriess.

The intro chpaters of my doctoral may also be helpful. Link: Google Drive/Waseda Repository

*Machine Learning/Deep Learning* :

An excellent repository already has listed most of the available free lecture notes/videos related to Machine Learning and Deep Learning. It goes by the name Deep Learning Drizzle. Below goes a more specific list prepared by me:

*Maths & More …*:

- Mathematics for Machine Learning. Thanks to Professor Marc Deisenroth for making this book completely free!
- Maths for ML: MIT Lecture Notes.
- Understanding Deep Learning by Dr. Simon Prince. Thanks to him for making the draft copy completely free!