Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- deep-learning
- mit
- self-driving-cars
- deep-reinforcement-learning
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Tutorials, assignments, and competitions for MIT Deep Learning related courses.
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Automatic extraction of relevant features from time series:
TensorFlow Tutorials with YouTube Videos
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Playing Pokemon Red with Reinforcement Learning
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Toturials coming with the "data science roadmap" picture.
Flax is a neural network library for JAX that is designed for flexibility.
The fastest way to create an HTML app
A course in reinforcement learning in the wild
Portfolio and risk analytics in Python
A scikit-learn compatible neural network library that wraps PyTorch
Create delightful software with Jupyter Notebooks
links to conference publications in graph-based deep learning
JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.
Performance analysis of predictive (alpha) stock factors
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
The Hunting ELK
Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
🛠 All-in-one web-based IDE specialized for machine learning and data science.
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier