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aialpha

Use unsupervised and supervised learning to predict stocks

alife-generativeart-projects

My ALife and Generative Art projects by Processing

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

chase

Automatic trading bot (WIP)

coronavirus-2020

Explore case numbers, deaths, recovered and active cases related to Coronavirus outbreak 2019/2020 (covid2019) in Pandas and in Jupyter notebook with MyBinder

cyclic-cellular-automata

d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

daily-stock-forecast

Daily Stock Forecasts using Machine Learning & Python

data-analysis

Data Science Using Python

datacamp_tutorials

finta

Common financial technical indicators implemented in Pandas.

generative-art

A hub for all of my generative art projects

generative_art

A collection of my *old* generative artwork, mostly with Processing in Python mode

generativeart

Create Generative Art with R

gmailapinachos

Gmail Api using python with domain counts of inbox data, csv export, count of domains

korona.ws

Map of confirmed coronavirus cases in Poland

lstm-learning

LSTM model to predict commodity price

pandas-technical-indicators

Technical Indicators implemented in Python using Pandas

rclone

"rsync for cloud storage" - Google Drive, Amazon Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Cloudfiles, Google Cloud Storage, Yandex Files

stock-prediction

stock-price-prediction

Stock Price Prediction

stock-price-prediction-1

Fall 18' Class Project for Artificial Intelligence

stock-price-prediction-2

Predicting stock price using historical data of a company, using Neural networks (LSTM).

stock_market_indicators

A small Python library with most common stock market indicators

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.

stocks

Programs for stock prediction and evaluation

stocktechnicalanalysis

Stock Technical Analysis - Python Tutorial

ta

Technical Analysis Library using Pandas (Python)

unity-poc

PDF instructions in asset

vsketch

Generative plotter art environment for Python