bkudor93's Stars
jonmest/breakoutfinder
A Python script for finding breakouts in historical data from stocks traded on the Nasdaq and NYSE.
matplotlib/mplfinance
Financial Markets Data Visualization using Matplotlib
cderinbogaz/inpredo
Inpredo is a Deep Learning tool which looks into financial charts and predicts stock movements.
leosmigel/analyzingalpha
redianmarku/Django-Twitter-Clone
A fully functional Twitter Clone built with Django.
samchaaa/alpaca_tech_screener
AI4Finance-Foundation/FinRL-Trading
For trading. Please star.
jayshah19949596/CodingInterviews
This repository contains coding interviews that I have encountered in company interviews
hackingthemarkets/candlestick-screener
web-based technical screener for candlestick patterns using Python and Flask
enggen/Deep-Learning-Coursera
Deep Learning Specialization by Andrew Ng, deeplearning.ai.
Kulbear/deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
lefman/mulan-extended
An extension of Mulan
arseniyturin/Capstone-Project
Predicting stock market movement with EDA and Keras
ray-project/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
llSourcell/Q-Learning-for-Trading
filangelos/qtrader
Reinforcement Learning for Portfolio Management
ucaiado/QLearning_Trading
Learning to trade under the reinforcement learning framework
AlphaSmartDog/DeepLearningNotes
机器学习和量化分析学习进行中
ZhengyaoJiang/PGPortfolio
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
georgezouq/awesome-ai-in-finance
🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.
awjuliani/cognition-course
Slides used in Cognitive Psychology course taught during summer 2015 at the University of Oregon
TheAlgorithms/Python
All Algorithms implemented in Python
borisbanushev/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.
rodler/quantcon2018
llSourcell/Reinforcement_Learning_for_Stock_Prediction
This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube
minimaxir/foursquare-venue-scraper
A Foursquare data scraper that gathers all venues within a specified geographic area.
shawn-terryah/Twitter_Geolocation
Geolocating twitter users by the content of their tweets
grayson-walker/Cannabis-Sentiment
Gauges legalization sentiment of recreationally illegal states using TextBlob for natural language processing of tweets from Twitter.
llSourcell/Learn_Data_Science_in_3_Months
This is the Curriculum for "Learn Data Science in 3 Months" By Siraj Raval on Youtube
llSourcell/Watch_Me_Build_a_Marketing_Startup
Subscribe to Siraj Raval on Youtube