sevenpen

sevenpen's Stars

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  27k287422.2k

• microsoft/LightGBM

  A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

  Language:C++16.7k4343.4k3.8k

• AI4Finance-Foundation/FinRL

  FinRL: Financial Reinforcement Learning. 🔥

  Language:Jupyter Notebook10k2027172.4k

• TA-Lib/ta-lib-python

  Python wrapper for TA-Lib (http://ta-lib.org/).

  Language:Cython9.7k3345921.8k

• DLR-RM/stable-baselines3

  PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

  Language:Python9k641.5k1.7k

• amueller/introduction_to_ml_with_python

  Notebooks and code for the book "Introduction to Machine Learning with Python"

  Language:Jupyter Notebook7.4k3661494.6k

• teddylee777/machine-learning

  머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

  Language:Jupyter Notebook2.6k646848

• jdwittenauer/ipython-notebooks

  A collection of IPython notebooks covering various topics.

  Language:Jupyter Notebook2.6k169151.5k

• amazon-science/chronos-forecasting

  Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting

  Language:Python2.5k2870281

• Nixtla/mlforecast

  Scalable machine 🤖 learning for time series forecasting.

  Language:Python8811314486

• ashishpatel26/Amazing-Feature-Engineering

  Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

  Language:Jupyter Notebook661151258

• kevinblighe/PCAtools

  PCAtools: everything Principal Components Analysis

  Language:R329146067

• Leci37/TensorFlow-stocks-prediction-Machine-learning-RealTime

  Predict operation stocks points (buy-sell) with past technical patterns, and powerful machine-learning libraries such as: Sklearn.RandomForest , Sklearn.GradientBoosting, XGBoost, Google TensorFlow and Google TensorFlow LSTM..Real time Twitter:

  Language:Python250261877

• hippocritical/strategies

  Language:Python348212

• gaugau3000/mc_sim_fin

  Montecarlo simulations/analysis for finance (equity simulator)

  Language:Python32407

• ZmicierGT/fcore

  Fcore Is an AI Framework for Financial Markets Analysis (Active Development).

  Language:Python23315

• emergentmethods/datasieve

  Adding coherence to the SKLearn pipeline

  Language:Python21022

• mrzdev/quest_deep_orderbook

  Store Binance Futures orderbook metrics in QuestDB leveraging local depth cache manager

  Language:Python41

• emergentmethods/flowdapt-cryptocast-plugin

  Language:Python3001

• freqtrade/ft-scikit-optimize

  Sequential model-based optimization with a `scipy.optimize` interface

  Language:Python3204

• knowusuboaky/feature_engineering

  Unleash the Power of Your Data with Feature Engineering: The Ultimate Python Library for Machine Learning Preprocessing and Enhancement

  Language:Jupyter Notebook3

• vishalbelsare/cointanalysis

  Python library for cointegration analysis. It carries out cointegration test and evaluates spread between cointegrated time-series based on scikit-learn API.

  Language:Python314

• DragonBtc93/generative-ai-for-beginners

  12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

  Language:Jupyter Notebook20

• emergentmethods/GLiNER

  Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 24

  1

• sevenpen/crypto-rl

  Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

  Language:Python10

• sevenpen/CryptocurrencyPrediction

  Predict Cryptocurrency Price with Deep Learning

  Language:Jupyter Notebook1000

• sevenpen/freqai

  An interface that lets users build, test, and deploy custom adaptive machine learning models in freqtrade. Mirrored development on github.com/freqtrade/freqtrade

  Language:Python1000

• sevenpen/machine-learning

  머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

  Language:Jupyter Notebook10

• sevenpen/strategies

  Custom trading strategies using the freqtrade framework

  Language:Python100

• sevenpen/tf_deep_rl_trader

  Trading Environment(OpenAI Gym) + PPO(TensorForce)

  1