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Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
quant
python
trading
orderbook
investment
market-maker
market-making
model-selection
limit-order-book
machine-learning
feature-selection
trading-strategies
algorithmic-trading
feature-engineering
orderbook-tick-data
quantitative-trading
market-microstructure
high-frequency-trading
backtesting-trading-strategies
Created
2016-07-21
158 commits to master branch, last one 2 years ago
Feature engineering package with sklearn like functionality
Created
2018-12-31
367 commits to main branch, last one about a month ago
For extensive instructor led learning
Created
2018-09-15
155 commits to master branch, last one 2 years ago
Machine Learning in R
Created
2013-08-29
4,812 commits to master branch, last one 4 months ago
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Created
2018-12-02
6 commits to master branch, last one 6 years ago
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
trading
algorithms
prediction
stock-data
data-science
stock-market
stock-prices
deep-learning
stock-trading
neural-network
stock-analysis
machine-learning
stock-prediction
feature-selection
feature-extraction
technical-analysis
feature-engineering
features-extraction
financial-engineering
stock-price-prediction
Created
2018-09-29
526 commits to master branch, last one 10 months ago
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Created
2020-04-03
1,075 commits to main branch, last one 4 months ago
Leave One Feature Out Importance
Created
2019-01-14
32 commits to master branch, last one 11 months ago
EvalML is an AutoML library written in python.
Created
2019-07-17
2,212 commits to main branch, last one about a month ago
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 alg...
Created
2019-02-19
13 commits to master branch, last one about a year ago
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.
Created
2020-11-29
346 commits to main branch, last one 8 months ago
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
Created
2021-05-16
30 commits to main branch, last one 10 months ago
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
Created
2021-04-16
130 commits to main branch, last one about a month ago
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Created
2019-01-22
76 commits to main branch, last one 3 months ago
Easy to use Python library of customized functions for cleaning and analyzing data.
Created
2020-03-25
886 commits to main branch, last one 29 days ago
Fast Best-Subset Selection Library
r
python
scikit-learn
cox-regression
machine-learning
feature-selection
linear-regression
multitask-learning
ordinal-regression
poisson-regression
logistic-regression
polynomial-algorithm
best-subset-selection
high-dimensional-data
classification-algorithm
sure-independence-screening
principal-component-analysis
robust-principal-component-analysis
sparse-principal-component-analysis
Created
2020-12-20
2,762 commits to master branch, last one 3 months ago
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Created
2016-09-19
283 commits to master branch, last one 3 years ago
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algor...
data-mining
correlations
data-science
spreadsheets
tabular-data
data-cleaning
data-analytics
data-cleansing
data-profiling
data-wrangling
data-engineering
data-exploration
anomaly-detection
feature-selection
data-preprocessing
feature-extraction
feature-engineering
knowledge-discovery
data-mining-algorithms
exploratory-data-analysis
Created
2020-04-09
1,495 commits to main branch, last one 18 days ago
本人多次机器学习与大数据竞赛Top5的经验总结,满满的干货,拿好不谢
Created
2019-10-11
73 commits to master branch, last one 3 years ago
Feature Selection using Genetic Algorithm (DEAP Framework)
Created
2017-11-12
36 commits to master branch, last one 4 years ago
Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & comme...
Created
2021-12-08
811 commits to main branch, last one 12 days ago
Awesome Domain Adaptation Python Toolbox
Created
2020-06-25
581 commits to master branch, last one about a month ago
This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
Created
2017-02-18
113 commits to master branch, last one 6 years ago
ML hyperparameters tuning and features selection, using evolutionary algorithms.
deap
automl
python
sklearn
help-wanted
scikit-learn
up-for-grabs
goodfirstissue
hyperparameters
model-selection
featureselection
good-first-issue
machine-learning
begginer-friendly
feature-selection
contributions-welcome
artificial-intelligence
evolutionary-algorithms
looking-for-contributors
hyperparameter-optimization
Created
2020-01-18
509 commits to master branch, last one 2 months ago
Code repository for the online course Feature Selection for Machine Learning
Created
2020-01-08
22 commits to main branch, last one 2 months ago
Data Science Feature Engineering and Selection Tutorials
Created
2021-05-07
68 commits to main branch, last one 2 years ago
This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.
wrapper
data-mining
bat-algorithm
cuckoo-search
classification
machine-learning
feature-selection
firefly-algorithm
genetic-algorithm
grey-wolf-optimizer
salp-swarm-algorithm
sine-cosine-algorithm
differential-evolution
harris-hawks-optimization
particle-swarm-optimization
flower-pollination-algorithm
whale-optimization-algorithm
Created
2020-12-25
38 commits to main branch, last one 3 years ago
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's ea...
python
grey-wolf
optimization
particle-swarm
machinelearning
machine-learning
subset-selection
feature-selection
genetic-algorithm
optimization-tools
grey-wolf-optimizer
supervised-learning
optimization-methods
evolutionary-algorithms
optimization-algorithms
machine-learning-algorithms
particle-swarm-optimization
Created
2020-07-11
264 commits to master branch, last one about a year ago
A Machine Learning Approach of Emotional Model
Created
2017-02-16
11 commits to master branch, last one 3 years ago
A fast xgboost feature selection algorithm
Created
2017-08-23
45 commits to master branch, last one 6 years ago