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airspace-hugo

Airspace theme (Hugo version)

arxiv-style

A Latex style and template for paper preprints (based on NIPS style)

cppn-gan-vae-tensorflow

Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.

cppn-tensorflow

Very Simple and Basic Implementation of Compositional Pattern Producing Network in TensorFlow

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

deep-learning-in-asset-pricing

https://arxiv.org/abs/1805.01104

deep-trading

Algorithmic trading with deep learning experiments

deep_learning_in_asset_pricing

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3350138

dl-4-tsc

Deep Learning for Time Series Classification

financeops

Research in investment finance with Python Notebooks

food100_yolo_tools

Python tools and configuration files for Food100 dataset DarkNet YOLO training

hugo-hero-theme

A modern business theme for Hugo.

lucid-sonic-dreams

matplotlib_for_papers

Handout for the tutorial "Creating publication-quality figures with matplotlib"

mbmlbook

Sample code for the Model-Based Machine Learning book.

neural-net-with-financial-time-series-data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

oil-natural-gas-price-prediction

Oil & Natural Gas prie prediction using ARIMA & Neural Networks

orbyter-cookiecutter

Dockerized ML Cookiecutter

orbyter-docker

Dockerfiles for images used as part of the Orbyter toolset

paper-list-of-time-series-forecasting-with-deep-learning

pdesbynns

This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means of neural networks using TensorFlow.

prefect

The easiest way to automate your data

pushgp-art

Using PushGP to evolve Compositional Pattern Producing Networks to create art in Clojure

pytorch-cppn-gan

An experiments with Compositional Pattern Producing Networks and Generative Adversarial Networks.

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

resume

LaTeX resume format

somepackage

Show how to structure a Python project.

stackbit-theme-azimuth

Azimuth is a sleek SaaS theme for Stackbit

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.

stylegan2

StyleGAN2 - Official TensorFlow Implementation with practical improvements