100-Days-Of-ML-Code
100DaysOfCode
Our great sponsors
| 100-Days-Of-ML-Code | 100DaysOfCode | |
|---|---|---|
| 3 | 1 | |
| 43,302 | 7 | |
| - | - | |
| 0.0 | 0.0 | |
| 4 months ago | about 3 years ago | |
| HTML | ||
| 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.
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
100DaysOfCode
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Week 1 of #100DaysOfCode Challenge | Our experience & Projects
While we were learning, we also wanted to apply everything we have learnt. To do that, we have been creating projects every single day and applying what we have learnt on that particular day. We have created a GitHub Repository for that as well. Check out the repo, give it a star and follow us on GitHub so that you can stay updated as we add new projects to the repo.
What are some alternatives?
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:
introduction-to-bash-scripting - Free Introduction to Bash Scripting eBook
Data-science-best-resources - Carefully curated resource links for data science in one place
30-Days-Of-HTML - A step by step guide to learn the concept of HTML, DOM tree, and web development in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
machine_learning_basics - Plain python implementations of basic machine learning algorithms
50-drops-of-php - Open source and free e-book, that collects collects more than 50 useful, unknown, underrated PHP functions or stuff discovered, used, and learned during PHP's daily use.
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
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.)
awesome-python-data-science - Probably the best curated list of data science software in Python.
SuperStyl - Supervised Stylometry
Py_Trans - Customize Python Syntax
carbon - :black_heart: Create and share beautiful images of your source code