ML-foundations
wordlescraper
| ML-foundations | wordlescraper | |
|---|---|---|
| 1 | 4 | |
| 2,984 | 0 | |
| - | - | |
| 5.4 | 0.0 | |
| 18 days ago | 9 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
ML-foundations
-
Worried about Calculus
As others have said, you won't need calculus immediately, but it's important that you make a good attempt at learning up to Calc3. I also didn't have a math heavy undergrad so it took a lot of self-study for me, but it's possible. Simulation has a great math boot camp at the beginning to review everything but you'll want to be prepped with Calc before that because that class is all calculus based probability. Some other good resources are the 3Blue1Brown videos on YouTube. They have a great series for both calc & linear algebra to talk through all the intuition with visuals. I also really like John Krohns series because you code through the math which is very applicable for us in this program. I only did his linear Algebra, but he has a whole series with Calc and probability, too. https://github.com/jonkrohn/ML-foundations
wordlescraper
- Daily Wordle #421 - Sunday, 14 Aug. 2022
- Only lost once (HOMER) but my 99% just turned back into 100% after hitting 200 played. Anyone else?
- 200 up this morning
-
Show & Tell - Ever wonder how your wordle score compares to others or why certain words are harder to guess? Check out my project (with Data Science predictive model for a given Word).
I'm open to feedback on any part of this project, including the Data Science part see Jupyter Notebook here.
What are some alternatives?
2D-Gaussian-Splatting - A 2D Gaussian Splatting paper for no obvious reasons. Enjoy!
facet - Human-explainable AI.
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
Basic-Mathematics-for-Machine-Learning - The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI
the-elements-of-statistical-learning - My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
cracking-the-data-science-interview - A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
ITC - Computer Science coursework and projects at Tec de Monterrey 👨🎓
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
algorithmica - A computer science textbook
Reinforcement_Learning - RL Algorithms with examples in Python / Pytorch / Unity ML agents
intel-processors - Datasets for All Processors Maufactured By Intel
linear-regression-from-scratch - A data science project for part II physics project E (surveying using stars)