Stars
Python Data Science Handbook: full text in Jupyter Notebooks
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 programs, usually short, of considerable difficulty, to perfect particular skills.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
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…
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Automatic extraction of relevant features from time series:
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Repository to store sample python programs for python learning
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
Useful functions, tutorials, and other Python-related things
Introduction to Deep Neural Networks with Keras and Tensorflow
An educational software system of a tiny self-compiling C compiler, a tiny self-executing RISC-V emulator, and a tiny self-hosting RISC-V hypervisor.
Deep Learning tutorials in jupyter notebooks.
General Assembly's 2015 Data Science course in Washington, DC
Bayesian Data Analysis demos for Python
Book and code for Think Complexity, 2nd edition
A tiny 1000 line LLVM-based numeric specializer for scientific Python code.
⏳🛡 Pythonic universal errors-and-erasures Reed-Solomon codec to protect your data from errors and bitrot. Includes a future-proof zero-dependencies pure-python implementation 🔮 and an optional spee…
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
Demonstration of MapR for Industrial IoT
Deliberate Practice for Learning Deep Learning
Hands-On Industrial Internet of Things, published by Packt
My solution to the Udacity Self-Driving Car Engineer Nanodegree Advanced Lane Lines project.
Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/
My solution to the Udacity Self-Driving Car Engineer Nanodegree Vehicle Detection and Tracking project.