Repository Index

Simple tutorials using Google's TensorFlow Framework

Performance analysis of predictive (alpha) stock factors

• finance
• python
• pandas
• numpy

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

• machine-learning
• deep-learning
• lstm
• human-activity-recognition

Quantitative analysis, strategies and backtests

• quantitative-finance
• quantitative-trading
• portfolio-management
• risk-management

Algorithms for outlier, adversarial and drift detection

• anomaly
• outlier
• concept-drift
• detection

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

• machine-learning
• python
• statistics
• scikit-learn

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

• high-frequency-trading
• limit-order-book
• python
• machine-learning

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

• deep-learning
• depth-prediction
• visual-odometry
• self-supervised-learning

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

• jupyter-notebook
• pandas
• federal-reserve
• gdp

🐧 Abuse of Google Colab for cracking hashes.

This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).

• aifinance
• fintech
• llama
• machine-learning

Use evolutionary algorithms instead of gridsearch in scikit-learn

Environment for reinforcement-learning algorithmic trading models

A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.

ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy

The repository host gives no description.

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

• feature-selection
• data-science
• python

Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.

TranslatedLLM teaching material for high school students: based on Karpathy's microgpt, for Google Colab

🏃 The go-to single-cell Foundation Model

• batch-correction
• cell-biology
• celltype-annotation
• denoising

AuShadha (औषध): Means medicine in Sanskrit. This is a Electronic Medical Records (EMR) and Public Health Management for small clinics written in Django and Dojo

The repository host gives no description.

Agentic LLM CTF to test prompt injection attacks and preventions