From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation. (by ahmedbahaaeldin)
ML-Papers-Explained
Explanation to key concepts in ML (by dair-ai)
| From-0-to-Research-Scientist-resources-guide | ML-Papers-Explained | |
|---|---|---|
| 9 | 4 | |
| 7,352 | 6,698 | |
| - | 0.6% | |
| 1.9 | 8.8 | |
| about 2 months ago | 4 days ago | |
| - | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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
Posts with mentions or reviews of From-0-to-Research-Scientist-resources-guide.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-31.
- 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.
-
Trending ML repos of the week 📈
9️⃣ ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
-
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.
-
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
-
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
ML-Papers-Explained
Posts with mentions or reviews of ML-Papers-Explained.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-31.
What are some alternatives?
When comparing From-0-to-Research-Scientist-resources-guide and ML-Papers-Explained you can also consider the following projects:
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
tuning_playbook - A playbook for systematically maximizing the performance of deep learning models.
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]
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
AnkiMath - A bachelor's degree in mathematics.
awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better.
100-Days-Of-ML-Code - 100 Days of ML Coding
ChatGPT - 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
From-0-to-Research-Scientist-resources-guide vs nanoGPT
ML-Papers-Explained vs tuning_playbook
From-0-to-Research-Scientist-resources-guide vs gpt_index
ML-Papers-Explained vs Mage
From-0-to-Research-Scientist-resources-guide vs AnkiMath
ML-Papers-Explained vs awesome-chatgpt-prompts
From-0-to-Research-Scientist-resources-guide vs 100-Days-Of-ML-Code
ML-Papers-Explained vs gpt_index
From-0-to-Research-Scientist-resources-guide vs awesome-chatgpt-prompts
ML-Papers-Explained vs ChatGPT
From-0-to-Research-Scientist-resources-guide vs tuning_playbook
ML-Papers-Explained vs nanoGPT