clokify for tracking time mpri https://github.com/josephmisiti/awesome-machine-learning https://x.com/AnantaVichara/media https://www.kaggle.com/code/ryanholbrook/a-single-neuron +discord docs: ML resources-
Ilya's paper recommendations-https://arc.net/folder/D0472A20-9C20-4D3F-B145-D2865C0A9FEE
full list-https://ml-resources.vercel.app/
https://karpathy.ai/zero-to-hero.html
books-
mathematics for machine learning- https://mml-book.github.io/book/mml-book.pdf
Linear Algebra and Its Applications by Gilbert Strang- https://rksmvv.ac.in/wp-content/uploads/2021/04/Gilbert_Strang_Linear_Algebra_and_Its_Applicatio_230928_225121.pdf
youtube-
3Blue1Brown-
Essence of linear algebra- https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
Essence of calculus- https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr
Andrej Karpathy- https://www.youtube.com/@AndrejKarpathy
Umar Jamil- https://www.youtube.com/@umarjamilai
Yannic Kilcher- https://www.youtube.com/@YannicKilcher
Sebastian Raschka- https://www.youtube.com/@SebastianRaschka
blogs-
Andrej Karpathy-https://karpathy.github.io/Jason Colah's Blog - https://colah.github.io Jason Wei-https://jasonwei.net/blog Scott Aaronson-https://scottaaronson.blog Jerry Tworek-https://millionintegrals.com Lilian Weng-https://lilianweng.github.io Nanda's Blogs-https://www.neelnanda.io/ Jake Tae's old Blogs - https://jaketae.github.io Sebastian Raschka- https://sebastianraschka.com distill-https://distill.pub/
Reinforcement Learning https://nptel.ac.in/courses/106106143
Artificial Intelligence: Knowledge Representation and Reasoning https://nptel.ac.in/courses/106106140
Artificial Intelligence Search Methods For Problem Solving https://nptel.ac.in/courses/106106226
Applied Accelerated Artificial Intelligence https://nptel.ac.in/courses/106106238
Artificial Intelligence https://nptel.ac.in/courses/106105077
Artificial Intelligence https://nptel.ac.in/courses/106105078
Pattern Recognition https://nptel.ac.in/courses/117108048
u said c++ then this book will be really helpful https://docs.nvidia.com/cuda/pdf/CUDA_C_Programming_Guide.pdf
Probabilistic Graphical Models
https://ermongroup.github.io/cs228-notes/
Okay so hers's the resources and my personal roadmap(as of now reflected in order ) on how i'm gonna learn the CUDA programming
- PMPP https://libgen.li/edition.php?id=146589140
- DLI course nvidia https://developer.nvidia.com/accelerated-computing-teaching-kit-syllabus#
- 100days of GPU challenge [example repo https://github.com/1y33/100Days ]
- (optional) Youtube https://www.youtube.com/@pmpp-book/videos 5.([later in journey) Second book for revision and programming : https://docs.nvidia.com/cuda/pdf/CUDA_C_Programming_Guide.pdf
https://www.youtube.com/watch?v=yBL7J0kgldU https://cs231n.stanford.edu/slides/2025/ https://www.youtube.com/c/T%C3%BCbingenML/playlists They have some good lectures on PML, and others. https://diffusion.csail.mit.edu/ https://youtu.be/Fk2I6pa6UeA?si=hT31G86DDX2S9sPO https://leetgpu.com/ https://ghoshadi.wordpress.com https://vijayrampeesa.wordpress.com/wp-content/uploads/2016/02/dms-txt-book.pdf https://artofproblemsolving.com/wiki/index.php/Olympiad_books?srsltid=AfmBOorVtcbNFUrFoOHOug-_EnD5nY-gzK9uMUfAR1rjLOZIxlySz2ju
Finished this lecture after days of procrastination https://www.youtube.com/watch?v=kCc8FmEb1nY
Over last 2 days:
- https://www.frozentux.net/iptables-tutorial/iptables-tutorial.html (c3)
- https://github.com/saminiir/level-ip (completed) HackerOne signup and some XSS reading and exploits. Finished Reading: https://archive.org/details/google-ai-agents-whitepaper/page/28/mode/1up?view=theater Reached and wrote notes till C6 of https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf Finished Karpathy Makemore (a bigram model)
- 5 exercises in the description box of the video
- https://www.youtube.com/watch?v=PaCmpygFfXo
Practical Machine Learning with Tensorflow https://nptel.ac.in/courses/106106213
Mathematics for Machine Learning https://nptel.ac.in/courses/111105489
Advanced Matrix Theory and Linear Algebra for Engineers https://nptel.ac.in/courses/111108066
Matrix Theory https://nptel.ac.in/courses/111108157
Essential Mathematics for Machine Learning https://nptel.ac.in/courses/111107137
Machine Learning and Deep Learning Fundamentals https://nptel.ac.in/courses/108103192
Machine Learning https://nptel.ac.in/courses/106106139
Machine Learning for Engineering and Science Applications https://nptel.ac.in/courses/106106198
Machine Learning And Deep Learning -- Fundamentals And Applications https://nptel.ac.in/courses/108103192
Deep learning - Part 1 https://nptel.ac.in/courses/106106184
Deep learning - Part 2 https://nptel.ac.in/courses/106106201
Natural Language Processing https://nptel.ac.in/courses/106105158
Natural Language Processing https://nptel.ac.in/courses/106101007
Applied Natural Language Processing https://nptel.ac.in/courses/106106211
Deep Learning for Computer Vision https://nptel.ac.in/courses/106106224
Deep Learning for Visual Computing https://nptel.ac.in/courses/108105103
Introduction to Large Language Models - Tanmoy Chakraborty https://nptel.ac.in/courses/106102576
Introduction to Large Language Models - Mitesh Khapra https://www.youtube.com/playlist?list=PLZ2ps__7DhBbaMNZoyW2Hizl8DG6ikkjo
Distributed Optimization and Machine Learning https://nptel.ac.in/courses/106101466
Bandit Algorithm https://nptel.ac.in/courses/110101145
Deep Generative Models https://www.youtube.com/playlist?list=PLL1s8qiaGy0LwIajdxKZr_FRL7KZeQK9r
ML resources-
Ilya's paper recommendations-https://arc.net/folder/D0472A20-9C20-4D3F-B145-D2865C0A9FEE
full list-https://ml-resources.vercel.app/
https://karpathy.ai/zero-to-hero.html
books-
mathematics for machine learning- https://mml-book.github.io/book/mml-book.pdf
Linear Algebra and Its Applications by Gilbert Strang- https://rksmvv.ac.in/wp-content/uploads/2021/04/Gilbert_Strang_Linear_Algebra_and_Its_Applicatio_230928_225121.pdf
youtube-
3Blue1Brown-
Essence of linear algebra- https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
Essence of calculus- https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr
Andrej Karpathy- https://www.youtube.com/@AndrejKarpathy
Umar Jamil- https://www.youtube.com/@umarjamilai
Yannic Kilcher- https://www.youtube.com/@YannicKilcher
Sebastian Raschka- https://www.youtube.com/@SebastianRaschka
blogs-
Andrej Karpathy-https://karpathy.github.io/Jason Colah's Blog - https://colah.github.io Jason Wei-https://jasonwei.net/blog Scott Aaronson-https://scottaaronson.blog Jerry Tworek-https://millionintegrals.com Lilian Weng-https://lilianweng.github.io Nanda's Blogs-https://www.neelnanda.io/ Jake Tae's old Blogs - https://jaketae.github.io Sebastian Raschka- https://sebastianraschka.com distill-https://distill.pub/
https://libgen.li/edition.php?id=146589140
https://developer.nvidia.com/accelerated-computing-teaching-kit-syllabus https://github.com/1y33/100Days https://docs.nvidia.com/cuda/pdf/CUDA_C_Programming_Guide.pdf https://cs231n.stanford.edu/slides/2025/ https://diffusion.csail.mit.edu/ https://www.youtube.com/c/T%C3%BCbingenML/playlists https://psidharth567.netlify.app/paper-breakdowns/native-sparse-attention--hardware-aligned-and-natively-trainable-sparse-attention https://x.com/psidharth567 https://x.com/psidharth567/status/1892513825355682108?t=L8ySzRQbrK35dSBPX2yw3A&s=19