mrdahdah Goto Github PK
Name: Mohamed Reda
Type: User
Company: QuantiAI
Bio: Quant Trader | Data Scientist
Location: Morocco
Name: Mohamed Reda
Type: User
Company: QuantiAI
Bio: Quant Trader | Data Scientist
Location: Morocco
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Examples of advanced Python programming techniques
Performance analysis of predictive (alpha) stock factors
I'm now a ALX Student, this is my first repository as a full-stack engineer.
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Code and Research Paper from the STEM Summer Research Internship :)
A project to explore the research in the paper: Creamer, Germán G. and Freund, Yoav, Automated Trading with Boosting and Expert Weighting (April 1, 2010). Quantitative Finance, Vol. 4, No. 10, pp. 401–420 . Available at SSRN: https://ssrn.com/abstract=937847
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
A curated list of awesome computer vision resources
A curated list of awesome Dash (plotly) resources
:boom: :chart_with_upwards_trend: A curated list of data science, analysis and visualization tools
A curated list of open finance and open banking resources
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Quant/Algorithm trading resources with an emphasis on Machine Learning
A curated list of awesome READMEs
:sunglasses: All the required resources to build your own startup
A complete computer science study plan to become a software engineer.
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
A collection of machine learning resources that I've found helpful (I only post what I've read!)
Study and implementation about deep learning models, architectures, applications and frameworks
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
An implementation of a deep learning recommendation model (DLRM)
A list of online resources for quantitative modeling, trading, portfolio management
A working example algorithm for scalping strategy trading multiple stocks concurrently using python asyncio
JPMorgan Finos
JP Morgan
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.