Aathirajan / tjsmafia-library-copy

Collection from the curated library of TJS Mafia Discord server

TJS Mafia Discord Library

Contributions

The members contributed to this library of the TJS Mafia Discord server. If you would like to contribute to this list to beautify/sort this easily or add additional resources, feel free to submit a PR, or you can add resources to the TJS Mafia Discord server's library channel, which will be updated here periodically.

Disclaimer

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Table of contents:

• Tools Lists
• Resources/books list
• For Copywriting
• Email Marketing
• General Libraries
• Hardware, IOT, etc.
• Math
• Programming, Dev, DSA, System Design, etc.
• Computer Networks, CPU, Sytems programming, etc.
• AI-ML, Data Science, Deep Learning, etc.
• UX/UI
• Blockchain Development

Tools list:

1. all-in online editor: https://www.kapwing.com/tools
2. simplest motion design tool: https://jitter.video/
3. slides/presentation deck + other edits: https://www.canva.com/
4. desktop whiteboard: https://excalidraw.com/
5. personal scheduling tool (free calendly alternative): https://zcal.co/
6. powerful form builder (google forms, typeform alternative): https://tally.so/
7. personal notebook: https://www.notion.so/

Resources/books list:

1. Learn Bitcoin, Ethereum, smart contracts, and decentralized finance: https://teachyourselfcrypto.com/
2. all about Economics: http://core-econ.org/the-economy/book/text/0-3-contents.html
3. my notion reading list: https://thejasonsamuel.notion.site/b12af56728b747b4bfd8ac371eec3e40?v=95b36f2b005a4f9ca4685db4012e6a73
4. A to Z computer science courses: https://github.com/Developer-Y/cs-video-courses#introduction-to-computer-science
5. why web-3 matters: https://twitter.com/cdixon/status/1442201621266534402?s=20&t=vkx7jrgn21hhMhfb-1e26w
6. Beginner's guide to crypto: https://creatoreconomy.so/p/curious-beginner-guide-to-crypto?utm_source=url
7. How to write a professional email: https://twitter.com/the_jasonsamuel/status/1342919959375056896?s=20
8. open-source flutter library: https://www.getwidget.dev/
9. full stack web dev course: https://www.theodinproject.com/paths/full-stack-javascript
10. python tutorial: https://youtube.com/playlist?list=PLRRsXF6W98Sudlltrf8rrxbPnzkHcHgG3
11. php tutorial: https://youtu.be/OK_JCtrrv-c
12. laravel fundamentals: https://www.youtube.com/playlist?list=PLFHz2csJcgk_3VJwzVoeyMuC1rdBcfiLv
13. laravel blade doc: https://laravel.com/docs/9.x/blade
14. flutter tutorial: https://www.youtube.com/watch?v=IfUjHNODRoM&list=PL6yRaaP0WPkVtoeNIGqILtRAgd3h2CNpT&index=3
15. seo tutorial: https://buildd.co/courses/startup-seo
16. psychologists view on ux design: https://link.medium.com/bgWSiu2Zrpb
17. basic guide on building online community: https://1drv.ms/b/s!AmKa3sbUtkOSk1tWgWRcbm8a29Cg?e=AhzOmX
18. on why design matters (doing more with less): https://www.youtube.com/watch?v=0jEj5cTJzZ0&ab_channel=dMASSnet
19. ikea effect: a ux case study: https://uxplanet.org/the-ikea-effect-a-ux-case-study-e30fb27df5cc
20. learn for free: https://www.selfschool.me/
21. learn system design: https://www.youtube.com/c/ByteByteGo
22. computer science roadmap: https://roadmap.sh/
23. search tool for software devs: https://codepilot.netlify.app/
24. Self-improvement resources: https://drive.google.com/drive/folders/1nGvGpXTnpogzuLX5Uc6UFRrfidypK2PC?usp=sharing

For Copywriting:

1. 50 pieces of copywriting advice: https://twitter.com/OneJKMolina/status/1533079377168240647?s=20&t=DqMRPm8xq6OoihvvvX_c7g
2. 31 Copywriting & Marketing Terms you Need To Know: https://www.alexcattoni.com/wp-content/uploads/2021/10/Free-Guide-Copy-Posse-Glossary-31-Copywriting-Marketing-Terms-You-Need-To-Know.pdf
3. Copywriting 101: How to craft a compelling story: https://davidlykhim.com/wp-content/uploads/2015/05/Copyblogger-Copywriting-101.pdf
4. Practice copywriting every day: https://www.copywritingprompts.com/
5. Fundamentals of copywriting: https://www.youtube.com/watch?v=mWNYE5yVOzk&feature=youtu.be&ab_channel=CopyThat!
6. Bob Bly's B2B Marketing handbook: https://www.bly.com/content/B2BMktgHdbk.pdf
7. How do you write an enticing homepage: https://www.julian.com/guide/startup/landing-pages
8. Tips guaranteed to improve your copywriting: https://twitter.com/jmoserr/status/1384510874417651718
9. 17 tips for copywriting: https://twitter.com/GoodMarketingHQ/status/1258052549246140416
10. 10 landing page copywriting tips for more conversions: https://twitter.com/jmoserr/status/1395025640022237186
11. 10+ copywriting mistakes: https://twitter.com/GrowthTactics/status/1416116689637240832
12. 20+ practical copywriting exercises to think and write like a pro: https://twitter.com/coreyhainesco/status/1392225233101283328
13. 10 copywriting formulas to increase conversions and clicks: https://twitter.com/jmoserr/status/1407346640206303242
14. 12 Formulas to write engaging headlines: https://marketingexamined.com/blog/formulas-to-write-engaging-headlines
15. Landing page teardown: https://www.demandcurve.com/teardowns
16. 7 tips for building a startup's landing page: https://twitter.com/Adityamttl/status/1498689548855160832?t=COtZIfPqidG134YC-pSmPg&s=19

Email Marketing:

1. Thread of actionable email insights: https://twitter.com/GrowthTactics/status/1341426684218753024
2. Email marketing case studies and breakdowns: https://emailmastery.org/
3. Collection of best cold email templates: https://betteroutreach.io/
4. Ultimate email marketing resources: https://www.emailstash.io/
5. Curated email templates for SAAS companies: https://saasemailtemplates.io/templates
6. Design resources for a better email: https://www.reallygoodemails.com/

General Libraries:

1. Z-library: https://z-lib.org/
2. Anna's archive: https://annas-archive.org/
3. Awesome opensource: https://awesomeopensource.com/
4. Connected Papers, A unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work: https://www.connectedpapers.com/

Hardware, IOT, etc.:

1. Hardware Security, Semi-invasive attacks, a new approach to hardware security analysis: https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-630.pdf

2. How to reverse engineer integrated circuits: https://www.youtube.com/watch?v=aHx-XUA6f9g

   Blog: https://www.youtube.com/watch?v=aHx-XUA6f9g Samy Kankar applied-hacking channel: https://www.youtube.com/user/s4myk Telegram Channel: https://t.me/hardwareSecurity

Math:

1. Middle school and high school math: https://artofproblemsolving.com/videos
2. AOPS math book: https://artofproblemsolving.com/store/list/aops-curriculum (search annas archive for free books)
3. Math Foundations by Norman Wildberger: https://youtube.com/playlist?list=PL5A714C94D40392AB&si=ijvCtn8YbeQfd7xx
4. Mathematical playground: https://mathigon.org/
5. Math is Fun (K-12): https://www.mathsisfun.com/

Programming, Dev, DSA, System Design, etc.:

1. Database Management Systems - Ramakrishnan Gehrke 3rd-Edition: https://github.com/Premiumlab/Database-Management-System-Ramakrishnan-Gehrke-3rd-Edition

2. Fundamentals of Cloud computing: https://github.com/learntocloud/learn-to-cloud

3. Top YouTube channels for competitive/Algorithmic Programming:

   • https://youtube.com/@Errichto
   • https://youtube.com/@PriyanshAgarwal
   • https://youtube.com/@WilliamFiset-videos - The Best for Network flows and graphs
   • https://youtube.com/@AlgorithmsLive
   • https://youtube.com/@vivekgupta3484 - Best Playlist on Dynamic Programming
   • https://youtube.com/@utkarshgupta9858
   • https://youtube.com/@codencode
   • https://youtube.com/@AlgosWithKartik
   • https://youtube.com/@SecondThread
   • https://youtube.com/@ColinGalen

4. Java book: https://gfgc.kar.nic.in/sirmv-science/GenericDocHandler/138-a2973dc6-c024-4d81-be6d-5c3344f232ce.pdf

5. Master programming by recreating your favorite technologies from scratch: https://github.com/codecrafters-io/build-your-own-x

6. Beginner resources for data structures and algorithms: Data Structures and Algorithms in Python Book by Michael H. Goldwasser, Michael T. Goodrich, and Roberto Tamassia

7. Primer on design patterns used in the Goodrich book:

   • https://refactoring.guru/design-patterns/python
   • https://github.com/mjwestcott/Goodrich

8. A lighter book on Algorithms: Grokking Algorithms by Aditya Y. Bhargava

9. Coding Interview:

   • https://github.com/jwasham/coding-interview-university
   • https://www.techinterviewhandbook.org/

10. UC Berkeley's cs61b is an introduction to data structures and algorithms course in Java: https://datastructur.es/

11. Algorithmic Thinking by Tim Roughgarden: https://youtube.com/@timroughgardenlectures1861?si=ReCn-5S6Zefokpb3

12. László Lovász's Discrete Mathematics book: https://cims.nyu.edu/~regev/teaching/discrete_math_fall_2005/dmbook.pdf

    • Course 01: https://www.math.cmu.edu/~ploh/2021-228.shtml
    • Course 02: https://youtube.com/playlist?list=PLgTkKBA6LRqYuuQ-LboerRblBoD_q_eUM

13. Discrete Mathematics course: https://cs.wheaton.edu/~tvandrun/dmfp/

14. Catalog of annotated code examples of all design patterns written in Python: https://youtube.com/playlist?list=PL8GFp_SBW-jdc7ZxO9SXkgZKKiNsD12M0&si=KRst6vtNLnxmuSgD

15. Intro to web dev in PHP

    • Harvard cs75 by David Malan of cs50: https://youtube.com/playlist?list=PL2puWTN1tf6LPXcpXx3WDcBMhcFM8sW2O
    • Web applications for everybody by Chuck Severance University of Michigan: https://youtube.com/playlist?list=PLlRFEj9H3Oj7FHbnXWviqQt0sKEK_hdKX
    • Book: https://milnepublishing.geneseo.edu/themissinglink/
    • PHP & MySQL: Novice to Ninja by Tom Butler
    • API Development with PHP: https://apisyouwonthate.com/books/

16. Intro to Web Dev in Python: https://runestone.academy/ns/books/published/webfundamentals/index.html

17. Catalogue of Python resources: https://www.fullstackpython.com/

18. Intro to Django web dev: https://wsvincent.com/books/

19. Intro to web-dev in Javascript

    • UC Berkley: https://youtube.com/@webdevatberkeley7546
    • https://fullstackdecal.com/
    • https://webatberkeley.notion.site/WDB-Dev-Design-Resources-b6d91c1b96834a8d8c86614e3c70bd74
    • https://www.webatberkeley.org/
    • University of Helsinki: https://fullstackopen.com/en/ (Introductory content on CI/CD using GitHub actions and containerization using docker)

20. Intro to Web security: https://web.stanford.edu/class/cs253/

    Lectures: https://youtube.com/playlist?list=PL1y1iaEtjSYiiSGVlL1cHsXN_kvJOOhu-

21. Learn SQL interactively: https://sqlbolt.com/

22. Database management systems:

    • https://www.reddit.com/r/learnSQL/comments/15yxqds/database_theory_learning_resources_for_the
    • https://www.reddit.com/r/learnSQL/comments/zybk5o/2023_update_the_best_resources_for_learning_sql
    • https://online.stanford.edu/courses/soe-ydatabases-databases
    • http://www.databaselecture.com/

23. Database internals, Architecture of a database system: http://db.cs.berkeley.edu/papers/fntdb07-architecture.pdf

24. Collection of significant DBMS papers: http://www.redbook.io/

25. Upper-level course on the internals of database management systems: https://15445.courses.cs.cmu.edu/fall2022/syllabus.html

26. Intro to database systems: https://m.youtube.com/playlist?list=PLSE8ODhjZXjaKScG3l0nuOiDTTqpfnWFf

27. Advanced database management systems: https://youtube.com/playlist?list=PLSE8ODhjZXjYzlLMbX3cR0sxWnRM7CLFn

28. Database group website: https://db.cs.cmu.edu/

29. Crash course in c: https://cs.uwaterloo.ca/~plragde/flaneries/IYMLC/

30. Introduction to C programming using C23: https://beej.us/guide/bgc/

31. Design recipes in c: https://postfix.hci.uni-hannover.de/files/prog1script/script.html

32. GDB: https://beej.us/guide/bggdb/

33. Concurrency in Python

    • https://superfastpython.com/learning-paths/
    • https://www.pythontutorial.net/python-concurrency/

34. Learning syntaxes of programming languages faster

    • https://hyperpolyglot.org/
    • https://exercism.org/
    • https://learnxinyminutes.com/

35. This intro to programming felt interesting pedagogy-wise: https://dcic-world.org/2022-08-28/index.html

36. Programming language theory

    • Course site https://cs.brown.edu/courses/csci1730/2022/index.html
    • Book -https://www.plai.org/ (edited)

37. System Design

    • https://github.com/donnemartin/system-design-primer
    • https://blog.bytebytego.com/p/free-system-design-pdf-158-pages
    • https://github.com/ByteByteGoHq/system-design-101
    • https://www.youtube.com/@SDFC

38. Software Architecture: https://aosabook.org/en/

39. Software engineering Free book + lectures

    • https://saasbook.info/
    • https://m.youtube.com/@saasbook/playlists

40. Lectures: https://www.cs.cornell.edu/courses/cs5150/2020sp/lectures.html

41. New syllabus video lectures: https://www.cs.cornell.edu/courses/cs5150/2022sp/schedule.html

42. Strivers A2Z DSA Course/Sheet - Crack Any FAANG or PBCs: https://takeuforward.org/strivers-a2z-dsa-course/strivers-a2z-dsa-course-sheet-2/

43. A curated list of Rust code and resources: https://github.com/rust-unofficial/awesome-rust

44. Building a web browser Book: https://browser.engineering/

45. A new browser from scratch: https://ladybird.dev/

46. Andreas Kling (who previously worked on the teams that built the KD browser and Safari) is building a new web browser from scratch, including the JS engine. He's been live coding the browser: https://youtube.com/playlist?list=PLMOpZvQB55be0Nfytz9q2KC_drvoKtkpS&si=OK_c1L1mgfsCN3JN

47. Jit compiler: https://youtube.com/playlist?list=PLMOpZvQB55bcTsXzRcBjHJJb52OGWwNjr&si=u2T_vkc4as5VgXKs

48. Js bytecode VM: https://youtube.com/playlist?list=PLMOpZvQB55beChggmvk-sUm8X_vSezpqL&si=H62Jt1Q0qagbNGRq

49. Visual web dev advanced HTML canvas and JS 2021: https://youtube.com/playlist?list=PLB0Tybl0UNfb3hTHPfEIg1SPw_-Ca9iIw&si=thq7P3s7mzDR-790

50. Visual web dev advanced HTML canvas and JS 2019: https://youtube.com/playlist?list=PLB0Tybl0UNfY_W97391GIxM8I27c4HKRm&si=NlXUHKwRO_1Td30i

51. Location-aware application development 2020: https://youtube.com/playlist?list=PLB0Tybl0UNfY1wfdwb8tlLBEz6H41P3aG&si=PCZbd2jyzNbmD06V

52. Single Page Applications without using Big 4 frameworks: https://hypermedia.systems/

53. Vanilla CSS, Kevin Powell: https://youtube.com/@KevinPowell?si=QZoUUaAG6ybCZ_m-

Computer Networks, CPU, Sytems programming, etc.:

1. Internet: https://www.internetsociety.org/internet/history-internet/brief-history-internet/

2. Open computer network books. The most rewarding book for a web developer: https://hpbn.co/

3. Beginner-friendly (no pre-requisite): https://beej.us/guide/bgnet0/

4. Other books to read if you have taken a course in computer systems

   • https://book.systemsapproach.org/
   • https://beta.computer-networking.info/syllabus/default/index.html

5. Good lectures from a now archives stanford mooc: https://youtube.com/playlist?list=PLoCMsyE1cvdWKsLVyf6cPwCLDIZnOj0NS&si=VD5AUumItoBwSjbP

6. simulation: https://netsim.erinn.io/

7. Exercises: https://gaia.cs.umass.edu/kurose_ross/wireshark.php

8. Guides:

   • https://iximiuz.com/en/series/computer-networking-fundamentals/
   • https://wizardzines.com/zines/tcpdump/
   • https://wizardzines.com/zines/networking/
   • https://wizardzines.com/networking-tools-poster/
   • https://jvns.ca/blog/2019/02/10/a-few-networking-tool-comics/
   • https://jvns.ca/juliasections/computer-networking/
   • https://launchschool.com/books/http
   • https://http2-explained.haxx.se/
   • https://http3-explained.haxx.se/en

9. Network programming in C: https://beej.us/guide/bgnet

10. Computer Networking, A top-down approach book by Jim Kurose, lectures from the author: https://m.youtube.com/@JimKurose/videos

11. Introduction to IoT: https://microsoft.github.io/IoT-For-Beginners/#/

12. Computer systems, What does a CPU do: https://cpu.land/

13. Free and open introductory computer systems books:

    • https://www.bottomupcs.com/
    • https://diveintosystems.org/book

14. CS61C Computer Organization

    • Course page: https://cs61c.org/
    • Lectures: https://www.youtube.com/@berkeley-cs61c/videos
    • Alternate resource for lectures (older lectures): https://learncs.me/ucb/cs61c

15. Systems programming. Introduction to computer systems

    • Course page: http://www.cs.cmu.edu/~213/
    • Book: http://csapp.cs.cmu.edu/3e/students.html
    • Lectures: https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID="b96d90ae-9871-4fae-91e2-b1627b43e25e"&maxResults=50
    • Exercises: http://csapp.cs.cmu.edu/3e/labs.html

16. CS 361

    • course page: https://www.cs.uic.edu/~ckanich/cs361/s21/
    • 2020 lectures: https://youtube.com/playlist?list=PLhy9gU5W1fvUND_5mdpbNVHC1WCIaABbP&feature=shared
    • 2021 lectures: https://youtube.com/playlist?list=PLhy9gU5W1fvVYcQUBZvS2wMcgsPnkQbJu&si=ped0IVsS72mTkX5N

17. Performance Engineering Of Software Systems(C programming): https://ocw.mit.edu/courses/6-172-performance-engineering-of-software-systems-fall-2018/pages/syllabus/

18. GPU programming: https://enccs.github.io/gpu-programming/4-gpu-concepts/

19. Design a CPU, learning computer architecture by building your own: https://www.udemy.com/course/design-a-cpu/

20. Nand to Tetris, building a modern computer from first principles: https://www.nand2tetris.org/

AI-ML, Data Science, Deep Learning, etc.

1. Getting started with reading ML Research Papers (Written by Ellfer Rudy, Discord username: ellferrudy)

So, starting, you must know basic and common mathematic notations. For that, ill suggest you learn them and use some cheat sheets as a reference.

• https://machinelearningmastery.com/basics-mathematical-notation-machine-learning/
• https://hci-kdd.org/wordpress/wp-content/uploads/2016/02/HOLZINGER-Machine-Learning-Notation.pdf
• https://nthu-datalab.github.io/ml/slides/Notation.pdf

While reading a paper, always pay attention to the abstract, figures, introductions, and conclusions; make sure you understand them before moving on to the next sections, as it's important to understand the context. Sometimes, you may not understand, but read it twice, and if you still don't understand them, then watch some videos or summaries on paper to get the context. There are plenty of YouTube channels where they walk through the papers and explain them completely.

After reading them, skim through the entire paper and write down everything you understood (leave the mathematical part for now). After a break, go deep into it and understand why they used certain hyperparameters, why they used the particular optimizer, loss function, metrics, etc., what the performance of the model compared to other SOTA models, and how it differs from them before that take a good time to understand the illustrations of the architecture.

Once you get what they say on paper, try to write the code from scratch or copy-paste the implemented code and fiddle with it. Make sure to keep track of the formula while writing its functions. In the long run, this will help you understand an equation and what it'll do while reading the paper.

2. Papers with Code: https://paperswithcode.com/

3. Arxiv Sanity: https://arxiv-sanity-lite.com/

4. Reference manager

   • https://www.mendeley.com/reference-management/reference-manager
   • https://www.zotero.org/
   • https://endnote.com/

5. YouTube channels that explain research papers

   • https://www.youtube.com/playlist?list=PL1v8zpldgH3pR7LPuidEZK68kS6AaU1y7
   • https://www.youtube.com/@hu-po
   • https://www.youtube.com/playlist?list=PLqFaTIg4myu8t5ycqvp7I07jTjol3RCl9
   • https://www.youtube.com/@AladdinPersson
   • https://www.youtube.com/@AndrejKarpathy
   • https://www.youtube.com/@TheAIEpiphany/videos
   • http://jalammar.github.io/
   • https://www.youtube.com/@umarjamilai
   • https://www.youtube.com/@AICoffeeBreak

6. From 0 to Research Scientist, Detailed and tailored guide for UG students in AI: https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide

7. Data Science best resources: https://github.com/tirthajyoti/Data-science-best-resources

8. A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep Learning by BentheCoder: https://github.com/benthecoder/yt-channels-DS-AI-ML-CS

9. Curated resources for learning ML from scratch: https://sgfin.github.io/learning-resources/#realA

10. Annotated PyTorch paper implementations: https://nn.labml.ai/index.html

11. New paper on image editing and manipulation, Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold: https://huggingface.co/papers/2305.10973

12. CSEP 546, Data Mining and Machine learning: https://www.youtube.com/watch?v=LnlW9gdjWfc&list=PLTPQEx-31JXgtDaC6-3HxWcp7fq4N8YGr

13. dair-AI ML-Youtube courses: https://github.com/dair-ai/ML-YouTube-Courses

14. Stanford CS230: Deep Learning - https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb

15. Deep Learning by Andreas Geiger - https://www.youtube.com/playlist?list=PL05umP7R6ij3NTWIdtMbfvX7Z-4WEXRqD

16. MIT 6.S191: Introduction to Deep Learning - https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

17. Deep Learning Course (NYU, Spring 2020) - https://www.youtube.com/playlist?list=PL80I41oVxglKcAHllsU0txr3OuTTaWX2v

18. Deep Learning - IIT Madras - https://www.youtube.com/playlist?list=PLyqSpQzTE6M9gCgajvQbc68Hk_JKGBAYT

19. Neural Networks: Zero to Hero - https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ (personal fav. playlist)

20. Practical Deep Learning for Coders 2022 - https://www.youtube.com/playlist?list=PLfYUBJiXbdtSvpQjSnJJ_PmDQB_VyT5iU

21. Supervised Machine Learning - https://www.coursera.org/learn/machine-learning

22. Building systems with ChatGPT: https://www.deeplearning.ai/short-courses/building-systems-with-chatgpt/

23. LangChain for LLM applications development: https://www.deeplearning.ai/short-courses/langchain-for-llm-application-development/

24. ChatGPT Prompt Engineering for Devs: https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/

25. Comprehensive list of awesome deep learning: https://github.com/Siddharth1India/Awesome-Deep-Learning

26. Understanding Deep Learning, by Simon J.D Prince: https://udlbook.github.io/udlbook/

27. Introduction to machine learning: https://www.youtube.com/watch?v=w2OtwL5T1ow&list=PLE6Wd9FR--EdyJ5lbFl8UuGjecvVw66F6

28. Tasks, stability, architecture, and compute: Training more effective learned optimizers and using them to train themselves: https://arxiv.org/abs/2009.11243

29. Stanford XCS224U: NLU I Intro & Evolution of Natural Language Understanding, Pt. 1 I Spring 2023: https://youtu.be/K_Dh0Sxujuc?list=PLoROMvodv4rOwvldxftJTmoR3kRcWkJBp&si=eDbam_QB6qYn00cO

30. Introduction to Machine Learning: https://sebastianraschka.com/blog/2021/ml-course.html

31. Applied Machine Learning: https://www.youtube.com/playlist?list=PL_pVmAaAnxIRnSw6wiCpSvshFyCREZmlM

32. Introduction to Deep Learning: https://sebastianraschka.com/blog/2021/dl-course.html

33. LLM Bootcamp: https://www.youtube.com/playlist?list=PL1T8fO7ArWleyIqOy37OVXsP4hFXymdOZ

34. UMass CS685: Advanced Natural Language Processing (Spring 2023) https://www.youtube.com/playlist?list=PLWnsVgP6CzaelCF_jmn5HrpOXzRAPNjWj

35. Efficient Deep Learning Computing(EfficientML.ai): https://www.youtube.com/playlist?list=PL80kAHvQbh-pT4lCkDT53zT8DKmhE0idB

36. Data science

    • introductory book: https://inferentialthinking.com/chapters/intro.html
    • Introductory Course page: https://www.data8.org/
    • Lectures: https://youtube.com/playlist?list=PL3juAj0fqNsLLBRFnTAby0VjByHoFb0qQ&si=lMqUUosH4w60KdsM
    • Intermediate Book: https://learningds.org/intro.html (This book was used for the course data100 in 2019. The book's first paragraph says it's an introductory resource, but the course is a follow-up to data8 and is an intermediate one and has other materials apart from this book.)
    • Intermediate Course page: https://ds100.org/su19/
    • The current version of the course uses this book: https://ds100.org/course-notes/
    • Advanced, The follow-up to data100 is data140 Book: http://prob140.org/textbook/content/README.html
    • Advanced Course page: http://prob140.org/ (data102 is the follow-up to data140)
    • Advanced Book: https://data102.org/fa23/resources/#textbooks-from-previous-data-science-courses

37. "This is a great little book to take you from “vaguely understand neural networks” to the modern broad state of practice. I saw very little to quibble with." - John Carmack

    • Book: https://fleuret.org/francois/lbdl.html
    • Course: https://fleuret.org/dlc/

38. Other advanced data science books: https://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/

UX/UI

1. The Component Gallery is an up-to-date repository of interface components based on examples from the world of design systems: https://component.gallery/

Blockchain development

1. These are sites that have web3 development courses for free.

• https://metaschool.so/courses
• https://www.metacrafters.io
• https://learnweb3.io/level-up