ML-foundations
2D-Gaussian-Splatting
| ML-foundations | 2D-Gaussian-Splatting | |
|---|---|---|
| 1 | 1 | |
| 2,984 | 292 | |
| - | - | |
| 5.4 | 6.4 | |
| 18 days ago | 13 days 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
2D-Gaussian-Splatting
-
[P] 2D Gaussian Splatting a great starting point for people who want to delve deeper
Github : https://github.com/OutofAi/2D-Gaussian-Splatting
What are some alternatives?
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
awesome-3D-gaussian-splatting - Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.
wordlescraper - Combine wordle statistics metrics from various locations, data science to correlate scores with words, and a front end to display the results.
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
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
SeeAI - Enabling computers to perform NLP on data obtained from advanced computer vision
ITC - Computer Science coursework and projects at Tec de Monterrey 👨🎓
TradeMaster - TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:
algorithmica - A computer science textbook
pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
Reinforcement_Learning - RL Algorithms with examples in Python / Pytorch / Unity ML agents
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.