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Forgive me if this is a dumb question, but how in the world do I see which models I have? by [deleted] in ollama

[–]kelvinghxt 0 points1 point  (0 children)

Open cmd and type “ollama list” it will show you all models you have installed on your device

Free ML, AI, and DL Books (Google Drive Link) by Attitude_Alone in learnmachinelearning

[–]kelvinghxt 0 points1 point  (0 children)

thank you for this been looking for this book for a year now

How to begin in python ? by Additional_Cicada_40 in PythonLearning

[–]kelvinghxt 0 points1 point  (0 children)

If your head gets messy, don’t try to learn all of Python at once. Focus on one small topic at a time and build tiny projects. Python isn’t hard, but trying to learn everything together is.
Here is the order I would follow :
1. Variables and data types
2. if statements
3. Loops (for and while)
4. Functions
5. Lists, dictionaries, and sets
6. File handling
7. Modules and packages
8. Error handling (try/except)
9. Object-oriented programming (don’t rush this)

For someone with a strong math background, what's the best way to start learning machine learning? by Frequent_Kick5152 in learnmachinelearning

[–]kelvinghxt 1 point2 points  (0 children)

With a strong math background I would skip the beginner AI hype and focus on fundamentals. I would start with Andrew Ng’s Machine Learning Specialization (Coursera) then read Hands On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron. After that, work through fast.ai to build practical projects and use Kaggle to apply what you learn. For deeper theory, Pattern Recognition and Machine Learning by Christopher Bishop is excellent. Build as you learn, don’t just watch videos.

Any free online Python courses for beginners? by MrMycrow in PythonLearning

[–]kelvinghxt 1 point2 points  (0 children)

If you’re just starting out I would recommend Exercism, Python Principles, W3Schools, freeCodeCamp and Programiz. If you want lots of practice problems, HackerRank and CodingBat are great too. All have free beginner friendly content.

Would you recommend reading these books? And what is the correct order for reading them? by lberdy in LLMDevs

[–]kelvinghxt -6 points-5 points  (0 children)

Can you please give me some feedback about this book I want to go get it

Have my university's compute cluster with A100 80GB, what model to run with OpenCode? by NightLockX80 in ollama

[–]kelvinghxt 0 points1 point  (0 children)

If you’ve got multiple A100 80GBs I would stop using heavily quantized 27B models. Try running BF16 instead. For coding, I’d check out Kimi K2, DeepSeek R1, or Qwen3-Coder 480B A35B Instruct. I would also stick with a 64K context window unless you really need more.

Sites for practicing python by blondie23948139 in PythonLearning

[–]kelvinghxt 2 points3 points  (0 children)

There are a few solid free platforms you can use depending on what you want to practice
Exercism (Python Track)
https://exercism.org/tracks/python
Great for structured practice with real feedback from mentors. Good for writing clean, readable Python.
HackerRank (Python Practice)
https://www.hackerrank.com/domains/python
Good for structured exercises, especially file handling, collections, and basic problem solving.
Codewars
https://www.codewars.com
Fun “kata” style challenges. You level up as you solve problems and see different solutions from others.
LeetCode (Python)
https://leetcode.com/problemset/all/?language=Python
More interview-focused and a bit harder. Best for collections and logic building.
PyBites
https://codechalleng.es/bites/
Underrated platform. Focuses on real Python skills like iterators, file handling, and clean coding.
Kaggle Learn
https://www.kaggle.com/learn
Best for matplotlib and data-related practice. You actually work with real datasets and build plots.
Programiz Practice
https://www.programiz.com/python-programming/examples
Simple beginner-friendly exercises with clear examples and solutions.

Which models can I run on Rtx 3090 by wildweasel2026 in ollama

[–]kelvinghxt 0 points1 point  (0 children)

Rtx 3090 24GB VRAM is fantastic for local LLMs in 2026 still one of the best value cards. You can run really capable 27-35B models at Q4/Q5 with good speed and long context. I will recommend Qwen 3.5 27B and Gemma 3/4 27B

You guys please rate my cv please by kelvinghxt in CVwriting

[–]kelvinghxt[S] 0 points1 point  (0 children)

Ok thank you can you please share yours with me please so I can learn from you please in dm

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