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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Flax is a neural network library for JAX that is designed for flexibility.
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained
Lectures on scientific computing with python, as IPython notebooks.
A simple notebook demonstrating prompt-based music generation via Mubert API
Fast and Easy Infinite Neural Networks in Python
A suite of image and video neural tokenizers
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
Differentiable, Hardware Accelerated, Molecular Dynamics
Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory …
Lightweight, useful implementation of conformal prediction on real data.
A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.
Companion site for the textbook Quantum Computing: An Applied Approach
IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)
OSS library that implements deep learning methods for partial differential equations and much more
Jupyter notebooks and other materials developed for the Columbia course APMA 4300
Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
Tutorial on "Modern Optimization Methods in Python"