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30-days-of-python

30 days of Python programming challenge is a step by step guide to learn Python programming language in 30 days.

actools

Alternative launcher for Assetto Corsa named Content Manager, and some utils as well.

awesome-free-deep-learning-papers

awesome-machine-learning

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

awesome-transformer-attention

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

bigquery-oreilly-book

Source code accompanying: BigQuery: The Definitive Guide by Lakshmanan & Tigani to be published by O'Reilly Media

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep_learning_object_detection

deeplearningbook

detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

developer-roadmap

Roadmap to becoming a web developer in 2019

dl-workshop-series

Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)

finplot

Performant and effortless finance plotting for Python

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

keras-segmentation-deeplab-v3.1

An awesome semantic segmentation model that runs in real time

lightweight-charts-python

Python framework for TradingView's Lightweight Charts JavaScript library.

mit-deep-learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

nevergrad

A Python toolbox for performing gradient-free optimization

openethereum

papers-with-code-sorted-by-stars

preprocessing-for-deep-learning

This is the notebook associated with the blog post:

python

All Algorithms implemented in Python

semantic-segmentation-demo

A Full stack Semantic Segmentation project using tensorflow, deeplab and dash

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

the-gan-zoo

A list of all named GANs!

vitmav45

Git repo for the BME deep learning course.