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A machine learning program that is able to recognize patterns inside Forex or stock data
Forex prediction using the NEAT algorithm.
A convenient gathering of useful and well-developed FreeCAD plugins made by the community.
A library of Parts for FreeCAD.
Fully-fledged Fundamental Analysis package capable of collecting 20 years of Company Profiles, Financial Statements, Ratios and Stock Data of 13.000+ companies.
Foreign Exchange Forecasting Model created for the paper "Can Interest Rate Factors Explain Rate Fluctuations?"
If you search for "Technical analysis and AI" in Persian you will find this post among the first 3 results of Google.
Ian Goodfellow's private research codebase
The Open Source Data Science Masters
A collection of easy-to-understand guides to programming tools
A few samples from Henry Carsten's book '101 Trading Ideas'
Samples code demonstrating how to use IbPy to extract information from Interactive Brokers API
Code to reproduce "imagenet in 18 minutes" experiments
Introducing neural networks to predict stock prices
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
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 filters, and more. All exercises include solutions.
Lean Algorithmic Trading Engine by QuantConnect (C#, Python, F#)
Learning to Learn in TensorFlow
In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.
Framework for algorithmic trading
Analysis and implementation of an LSTM Neural Network to predict foreign exchange of currencies.
Tons of fun with text and recurrent neural networks! Let your computer read a book and tell you its own story. 🤣
Python machine learning applications in image processing and algorithm implementations including Gaussian Mixture Model, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, K Nearest Neighbors, K Means, Naive Bayes, Gaussian Discriminant Analysis, Newton Method, Gradient Descent
Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.
:computer: Make machines learn so that you don't have to program them; The ultimate list
Machine Learning for finance and investment introduction
A complete daily plan for studying to become a machine learning engineer.
Examples on building machine learning models
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.