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fes

Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson

financial-statements-text-analysis

Documentation and code for downloading, cleaning, munging, and analyzing financial statements filed by publicly traded companies with the SEC

finrl

FinRL: Financial Reinforcement Learning. 🔥

flexgen

Throughput-oriented systems for large language models on commodity GPUs.

google-research

Google Research

gptq-for-llama

4 bits quantization of LLaMa using GPTQ

hakank

My public programs and models - mostly combinatorial problems and puzzles

hierarchicalforecast

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

highfrequency

The highfrequency package contains an extensive toolkit for the use of highfrequency financial data in R. It contains functionality to manage, clean and match highfrequency trades and quotes data. Furthermore, it enables users to: calculate easily various liquidity measures, estimate and forecast volatility, and investigate microstructure noise and

hn_summary

Summarizes top stories from Hacker News using a large language model and posts them to a Telegram channel.

ib_insync

Python sync/async framework for Interactive Brokers API

ibc

Automation of Interactive Brokers TWS. You can download the latest release here: https://github.com/ibcalpha/ibc/releases/latest

ibrokers

R API to Interactive Brokers Trader Workstation

kaggle-solutions

🏅 Collection of Kaggle Solutions and Ideas 🏅

kaggle-web-traffic

1st place solution

kalman-and-bayesian-filters-in-python

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.

knowledge-graph-tutorials-and-papers

Insightful Tutorials and Papers about Knowledge Graphs

knowledge_gpt

Accurate answers and instant citations for your documents.

langchain

⚡ Building applications with LLMs through composability ⚡

lean

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

machine-learning-for-algorithmic-trading-second-edition_original

Machine Learning for Algorithmic Trading, Second Edition - published by Packt

micro_price

microprediction

If you can measure it, consider it predicted

microprice

modern-data-mining-algorithms-in-cpp-cuda-c

Source Code for 'Modern Data Mining Algorithms in C++ and CUDA C' by Timothy Masters

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

natural-language-processing-with-flair

Natural Language Processing with Flair, published by Packt

nautilus_trader

A high-performance algorithmic trading platform and event-driven backtester

onload

OpenOnload high performance user-level network stack