Imperial-College-Data-Science-Society / Challenges
ICDSS Advanced Data Science Team Challenges 2020-2021
☆16Updated last year
Related projects: ⓘ
- ICDSS Machine Learning Workshop Series: Machine Learning APIs☆10Updated 6 years ago
- ICDSS Machine Learning Workshop Series: Neural Networks☆17Updated 6 years ago
- The Incredible TensorFlow 2: a curated list of tutorials, papers, projects, communities and more relating to TensorFlow 2.☆29Updated 4 years ago
- AI Core NLP Course☆20Updated 4 years ago
- Hypothesis and statistical testing in Python☆61Updated 4 years ago
- Applied Machine Learning with Python☆76Updated 5 months ago
- [Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. K…☆9Updated last year
- Explorations of survival analysis in Python☆50Updated last year
- Test LightGBM's Dask integration on different cluster types☆12Updated 2 weeks ago
- Introductory tutorial notebooks for learning data science, as part of the Data Science in Practice materials.☆75Updated last year
- Workshop on Bayesian inference using PyMC☆26Updated 3 years ago
- ☆11Updated 2 years ago
- Notebooks for Fastai Viusal Guide☆25Updated last year
- Jupyter Notebook for the "Scientific Computing in Python: Introduction to NumPy and Matplotlib" blog article☆44Updated 3 years ago
- ☆10Updated this week
- Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.☆20Updated 2 years ago
- Datasets associated with pyprobml☆19Updated last year
- A set of notes, in the form of a simple Github Pages site, which will serve as a complete crash course on the various areas of mathematic…☆61Updated 4 years ago
- The 2020 Version of the Deep Learning Course☆8Updated 4 years ago
- Tutorials for the Machine Learning for Time Series class - Master MVA (2021/2022)☆10Updated 2 years ago
- Experiments on structure learning of Bayesian Networks with emphasis on finding causal relationship☆9Updated 5 years ago
- ☆15Updated 2 years ago
- ☆15Updated this week
- Guidelines for the responsible use of explainable AI and machine learning.☆17Updated last year
- Workshop materials created for the Data Science Club at UWaterloo.☆17Updated 2 years ago
- Statistics and Machine Learning in Python☆67Updated 3 years ago
- Repo for the course "Fundamentals of Deep Learning with Pytorch"☆39Updated 2 years ago
- ☆10Updated 4 years ago
- Companion code for my PyData talk: "Introduction to Probabilistic Programming with PyMC3"☆13Updated 5 years ago
- Data science and ML with Dask☆13Updated 3 years ago