Hadar933 / Deep-Reinforcement-LearningLinks
DRL university course lecture notes & exercises
☆86Updated 2 years ago
Alternatives and similar repositories for Deep-Reinforcement-Learning
Users that are interested in Deep-Reinforcement-Learning are comparing it to the libraries listed below
Sorting:
- Representation Learning MSc course Summer Semester 2023☆80Updated last year
- Streamline scikit-learn model comparison.☆145Updated 2 years ago
- Lightning Bits: Engineering for Researchers repo☆132Updated 2 years ago
- Lecture Notes on Statistical Inference☆76Updated 8 months ago
- ☆152Updated 3 years ago
- ☆199Updated last month
- Kaggle Pipeline for tabular data competitions☆207Updated 11 months ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆90Updated last year
- Host repository for the "Reproducible Deep Learning" PhD course☆406Updated 3 years ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆140Updated 11 months ago
- ☆17Updated 3 years ago
- A curated list of awesome fastai projects/blog posts/tutorials/etc.☆172Updated 3 years ago
- A resource list for causality in statistics, data science and physics☆264Updated 2 weeks ago
- ☆33Updated 9 months ago
- ☆25Updated 5 years ago
- Statistics and Mathematics for Machine Learning, Deep Learning , Deep NLP☆82Updated 3 years ago
- ☆25Updated 2 years ago
- ☆115Updated last year
- This course is an overview of applied causal inference.☆49Updated last month
- Repo for ML Models built from scratch such as Self-Attention, Linear +Logistic Regression, PCA, LDA. CNN, LSTM, Neural Networks using Nu…☆49Updated 4 months ago
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.☆65Updated 4 months ago
- Course for Interpreting ML Models☆52Updated 2 years ago
- Materials for the AI Dev 2024 conference workshop "Deploy and Monitor ML Pipelines with Python, Open Source, and Free Applications"☆94Updated this week
- Learn how to create reliable ML systems by testing code, data and models.☆87Updated 2 years ago
- Bayesian Bandits☆68Updated last year
- ☆34Updated 4 months ago
- Production-Ready Applied Deep Learning☆90Updated last year
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆27Updated 11 months ago
- The best repository showing why SMOTE and resampling methods might not be the answer for imbalanced data problems☆46Updated 3 months ago
- ☆285Updated 2 years ago