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ad-effectiveness-report

adv-financial-ml-marcos-exercises

Exercises of the book: Advances in Financial Machine Learning by Marcos Lopez de Prado

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

advanced-data-analytics-using-python

Source Code for 'Advanced Data Analytics Using Python' by Sayan Mukhopadhyay

advanced-data-science

Assignments of Machine Learning in Python

advanced-prediction-of-multi-stage-continuous-flow-manufacturing-process

Created data regression models to predict 15 unknown variables within 4% error at any plant condition. Denoised 11000 x 115 dataset, leading to 70% improvement in prediction accuracy. Used data engineering to produce features that were relevant to the target variables. Produced confusion matrices to determine relevant features for machine learning. Final prediction horizon of four times dataset timescale to within 5% error

algorithmic-trading-with-python

Source code for Algorithmic Trading with Python (2020) by Chris Conlan

algotrading-forecasting-test

Coding for testing Prophet time series forecasting for stock.

alpaca-algotrading--legacy-

Engineered and backtested strategies using a variety of indicators and custom features. Optimized buy/sell conditions through custom optimization algorithm. Discovered most significant features through machine learning. Created Heroku app to maintain code during downtime. Implemented a portfolio manager that automatically handles, scales, and visualizes financial gains and losses. Current design yields an SQN of 8.9-9.2.

alpacaexamples

Example code repository

alphafold

Open source code for AlphaFold.

alphavantage_alpaca_integration

This is a repository for implementing data requisition for algotrading using Alphavantage standard API for intraday data and implementing said data into a trading script through the Alpaca Broker.

amazon-sales-analysis-nda-approved

Provided actionable insights to maximize sales of specific undersupplied merchandise. Created data features to specify unmet demand and oversupply. Determined exact times of seasonality to maximize profits by targeted advertisements. Cleaned unstable data to correctly visualize realistic sales data. Pinpointed specific models and categories of merchandise for production and cancellation. Estimated dropship quantity to assist in maintaining available stock of specific models on Amazon.

amd_gpu_ml

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning

analysis-and-time-series-forecasting-covid-south-korea-

anthropic-cookbook

A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.

anthropic-sdk-python

applied-ml

📚 Papers of companies sharing their work on applied data science & machine learning.

applied-reinforcement-learning-w-python

Source Code for 'Applied Reinforcement Learning with Python' by Taweh Beysolow

automatic_timeline_setup

awesome-astra-docs

awesome-data-centric-ai

Open-Source Software, Tutorials, and Research on Data-Centric AI 🤖

awesome-open-data-centric-ai

Curated list of open source tooling for data-centric AI on unstructured data.

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

basic-time-series-sales-forecasting

bayesian-machine-learning

Notebooks about Bayesian methods for machine learning

bayesianepisodiccontrol

Proof-of-concept code for Bayesian Episodic Control

bayesianrl

Some example code for the "Introduction to Bayesian Reinforcement Learning" presentations