From-0-to-Research-Scientist-resources-guide
100-Days-Of-ML-Code
| From-0-to-Research-Scientist-resources-guide | 100-Days-Of-ML-Code | |
|---|---|---|
| 9 | 3 | |
| 7,352 | 43,337 | |
| - | - | |
| 1.9 | 0.0 | |
| about 2 months ago | 4 months ago | |
| - | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
From-0-to-Research-Scientist-resources-guide
- Roadmap para Inteligência artificial.
- From Zero to Research Scientist - Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
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Trending ML repos of the week 📈
9️⃣ ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
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Free ML Resources on the web
I am sharing with you this https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide so that you can find all the relevant books and courses that other people tried. And are insightful based upon reviews. Happy learning.
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Book Before Papers?
This guide is quite comprehensive for taking courses and reading papers From-0-to-Research-Scientist-resources-guide. Again as stated in the comments working on problems is more rewarding, and you learn more, but I would say first make sure you understand the fundamental principles.
- Mathematics and Machine Learning Free Resources
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Github ML resources list
Hello all, Iam a TA at some university and created a list for students for starting AI. I would love some feedback from experienced people on how to improve this plan so i can help as much as i can of people to learn AI. https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
100-Days-Of-ML-Code
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Top 10 GitHub Repositories Every Developer Should Bookmark in 2024
2) 100 Days of ML Code: Embark on a 100-day journey into the fascinating world of machine learning with this structured curriculum. Packed with bite-sized coding challenges and real-world projects, this repository will transform you from a coding novice to a confident ML enthusiast. (https://github.com/Avik-Jain/100-Days-Of-ML-Code)
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✨ 5 Best GitHub Repositories to Learn Machine Learning in 2022 for Free 💯
1️⃣ 100 Days Of ML Code
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The Ultimate Resource Guide for Your Next 100 Days of Code
ML: 100-Days-Of-ML-Code
What are some alternatives?
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
machine_learning_basics - Plain python implementations of basic machine learning algorithms
AnkiMath - A bachelor's degree in mathematics.
Data-science-best-resources - Carefully curated resource links for data science in one place
awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better.
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
tuning_playbook - A playbook for systematically maximizing the performance of deep learning models.
dive-into-machine-learning - Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
ChatGPT - 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
100DaysOfCode - A GitHub Repo for my #100DaysOfCode challenge projects