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Sibirtsev
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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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 ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
💿 Free software that works great, and also happens to be open-source Python.
A collection of various deep learning architectures, models, and tips
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…
PRML algorithms implemented in Python
Automatic extraction of relevant features from time series:
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Notebooks and code for the book "Introduction to Machine Learning with Python"
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
A course in reinforcement learning in the wild
An annotated implementation of the Transformer paper.
Python code for common Machine Learning Algorithms
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
Tutorials for creating and using ONNX models
Open Content for self-directed learning in data science
Introduction to Deep Neural Networks with Keras and Tensorflow
A high performance implementation of HDBSCAN clustering.
A collection of IPython notebooks covering various topics.
Code for the Make Your Own Neural Network book
InferSent sentence embeddings
Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+
