Implementations for Adances In Financial Machine Learning
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Updated
Feb 9, 2020 - Python
Implementations for Adances In Financial Machine Learning
Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning
Advanced Financial Machine Learning Toolbox
A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.
Setting up monitor windows to track the stock price movement directions and make prediction on future price movement in a short time.
Implementations of Genetic Methods for Financial Machine Learning Applications
Genetic Programming and Neural Networks for Financial Predictive Modeling.
Convex linear models, Linear Regression, Logistic Regression, and Support Vector Machines, to test convexity and performance by using non-linear endogenous features in time series data.
Python library for building financial machine learning models.
Apply a Transformer-based model for financial data prediction.
Dissertation - Individual (305AAE/306AAE) Project
A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.
A set of financial analytics projects with python.
How to use sentiment analysis to predict stock's sentiment
Standard & Poor's 500 Financial Analysis
Comprehensive analysis of various ML models to detect fraud in financial transactions.
A tool to detect whether numerals present in Financial Texts are in-claim or out-of-claim
Numerai's Next Top Model
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