GitHub topics: feature-engineering

arsentag/Retail_Credit_Scoring_Model

Language: Jupyter Notebook - Size: 24 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

Machine-Learning-Related-Projects/Real-Fake-Job-Post

Real-Fake-Job-Post

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kurtispykes/fraud-detection-project

A mono-repository containing a packaged machine learning model and simple REST API.

Language: Jupyter Notebook - Size: 130 KB - Last synced at: 7 days ago - Pushed at: over 3 years ago - Stars: 14 - Forks: 9

Moez-lab/House-Price-Prediction

A Machine Learning project that predicts California house prices using Linear Regression and Random Forest. It includes data preprocessing, feature engineering, visualizations, and model evaluation with hyperparameter tuning using GridSearchCV.

Language: Python - Size: 396 KB - Last synced at: 1 day ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0

Ramtin-Karbaschi/HousingPriceAdvance_KERASmodel

Advanced machine learning implementation for housing price prediction, utilizing statistical modeling to analyze property attributes and their market impacts. Features comprehensive data visualization, feature engineering, and model comparison techniques.

Language: Jupyter Notebook - Size: 494 KB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 1 - Forks: 0

DAGWorks-Inc/hamilton

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

Language: Jupyter Notebook - Size: 75.8 MB - Last synced at: 17 days ago - Pushed at: about 1 month ago - Stars: 2,108 - Forks: 143

CryAndRRich/kaggle-contest

Collection of my submissions for the Kaggle competitions I have participated in

Language: Python - Size: 18.1 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0

Hands-On-Fraud-Analytics/Chapter-10-Advanced-Feature-Engineering-Techniques-for-Fraud-Analytics

Advanced Feature Engineering Techniques for Fraud Analytics

Language: Jupyter Notebook - Size: 3.42 MB - Last synced at: 17 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

mljar/mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Language: Python - Size: 9.44 MB - Last synced at: 17 days ago - Pushed at: 26 days ago - Stars: 3,144 - Forks: 419

archie-cm/Churn-Analysis-Ecommerce-Customer

The objective of this project to is to predict customer churn, loss opportunity and provide recommendations to the business team so the company can implement a customer persona in retention strategy and can monitoring throught dashboard interactive.

Language: Jupyter Notebook - Size: 15.1 MB - Last synced at: 17 days ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 3

StoicHistory/soc-predict

This project uses an Artificial Neural Network (ANN) to predict battery charge levels (SoC)

Language: Jupyter Notebook - Size: 608 KB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

NVIDIA-Merlin/NVTabular

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.

Language: Python - Size: 98.4 MB - Last synced at: 9 days ago - Pushed at: 8 months ago - Stars: 1,079 - Forks: 146

Ehsan-Behzadi/Online-Retail-Data-Analysis-and-Preprocessing

This project analyzes and preprocesses the Online Retail dataset to uncover insights into customer purchasing behaviors, sales trends, and product performance. It includes data cleaning, exploration, and visualization, with the goal of enhancing understanding of online retail dynamics.

Language: Jupyter Notebook - Size: 1.86 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

cod3licious/autofeat

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Language: Python - Size: 1 MB - Last synced at: 14 days ago - Pushed at: about 2 months ago - Stars: 514 - Forks: 63

22P31A0512/Sentimental-Analysis

Build a model to classify text as positive, negative, or neutral. Apply NLP techniques for preprocessing and machine learning for classification. Aim for accurate sentiment prediction on various text formats.

Language: Jupyter Notebook - Size: 280 KB - Last synced at: 17 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

evinism/mistql

A query / expression language for performing computations on JSON-like structures. Tuned for clientside ML feature extraction.

Language: TypeScript - Size: 3.4 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 363 - Forks: 19

djsahil/VWAPForecast

Equities VWAP Forecasting

Language: R - Size: 64.8 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0

kumarritik24/Uber-Trip-Analysis-in-NYC

Visual exploration of Uber ride patterns in NYC using Python. Identifies peak demand times, geospatial hotspots, and weekday vs. weekend behavior trends.

Language: Jupyter Notebook - Size: 8.29 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 1 - Forks: 0

kumarritik24/Titanic-Survival-Prediction-using-Machine-Learning

This project applies Machine Learning techniques to predict the survival of Titanic passengers. It explores various data preprocessing, visualization, and model-building techniques to enhance predictive accuracy.

Language: Jupyter Notebook - Size: 802 KB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0

monetjoe/EMelodyGen

Emotionally Conditioned Melody Generation in ABC Notation

Language: Python - Size: 1.69 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 9 - Forks: 0

Lethe4564518/TemporalFusionTransformer-model

Temporal Fusion Transformer model實作，目的為熟悉特徵工程、建模流程及預測結果視覺化，並深入研究模型架構與內部邏輯，強化對新模型的理解能力。當前仍在優化中

Language: Python - Size: 7.12 MB - Last synced at: 19 days ago - Pushed at: 20 days ago - Stars: 1 - Forks: 0

Abdulabin/Diabetes-Prediction-Model

A machine learning model that predicts diabetes in patients based on various health indicators using logistic regression. Features include data analysis, visualization, and an interactive prediction system.

Language: Jupyter Notebook - Size: 174 KB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

duxuhao/Feature-Selection

Features selector based on the self selected-algorithm, loss function and validation method

Language: Python - Size: 10 MB - Last synced at: 16 days ago - Pushed at: about 6 years ago - Stars: 678 - Forks: 199

mohannadhendi/social-media-post-prediction

A complete end-to-end machine learning pipeline to predict total social media post interactions using advanced regression models

Language: HTML - Size: 1.33 MB - Last synced at: 13 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

sberbank-ai-lab/LightAutoML 📦

LAMA - automatic model creation framework

Language: Python - Size: 23.4 MB - Last synced at: 10 days ago - Pushed at: about 3 years ago - Stars: 925 - Forks: 96

sergio11/diabetes_prediction_ml

Predicting diabetes using machine learning models based on medical data 📊💉. The goal is to create an accurate and reliable diagnostic tool for early detection 🏥🤖.

Language: Jupyter Notebook - Size: 13.6 MB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 2 - Forks: 2

MahdiKh03/Transaction-Fraud-Detection

A machine learning project to predict fraudulent transactions using supervised learning algorithms, along with feature engineering techniques.

Language: Jupyter Notebook - Size: 201 KB - Last synced at: 2 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

abu14/transaction-anomaly-detection

An end to end fraud detection model to identify anomalies within transactions.

Language: Jupyter Notebook - Size: 420 KB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

mshahzad021/credit-card-fraud-detection

Exploratory data analysis with SQL and predictive modeling in Python to identify fraudulent credit card transactions. Includes feature engineering, fraud pattern insights, and machine learning evaluation.

Language: Python - Size: 2.05 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

sadiq18/PredictPodcastListeningTime

Kaggle contest to predict listening time of a podcast episode.

Language: Jupyter Notebook - Size: 23.1 MB - Last synced at: 8 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

fraunhoferportugal/tsfel

An intuitive library to extract features from time series.

Language: Python - Size: 39.7 MB - Last synced at: 19 days ago - Pushed at: 7 months ago - Stars: 1,001 - Forks: 153

MatsMoll/aligned

The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt

Language: Python - Size: 6.08 MB - Last synced at: 11 days ago - Pushed at: about 2 months ago - Stars: 58 - Forks: 2

KxSystems/mlnotebooks

Demonstration notebooks for Machine Learning

Language: Jupyter Notebook - Size: 47.8 MB - Last synced at: 2 days ago - Pushed at: 10 months ago - Stars: 63 - Forks: 46

sanjurajveer/Fraud_detection

Model for categorising transactions into fraud or not

Language: Jupyter Notebook - Size: 6.34 MB - Last synced at: 22 days ago - Pushed at: 23 days ago - Stars: 0 - Forks: 0

ChenTaHung/Monotonic-Optimal-Binning

Monotonic Optimal Binning algorithm is a statistical approach to transform continuous variables into optimal and monotonic categorical variables.

Language: Python - Size: 7.44 MB - Last synced at: 16 days ago - Pushed at: over 1 year ago - Stars: 17 - Forks: 2

Cyberoctane29/TikTok-Claims-Classification-End-to-End-Analysis-and-Modeling

This project analyzes TikTok videos to classify claims vs. opinions using Python. It includes EDA, statistical tests, logistic regression, and ML models (Random Forest, XGBoost) to support content moderation. Built with pandas, scikit-learn, and Tableau, the solution helps TikTok automate content review and enhance moderation efficiency.

Language: Jupyter Notebook - Size: 24.6 MB - Last synced at: 18 days ago - Pushed at: 24 days ago - Stars: 5 - Forks: 0

v1tzor/TimePlanner

Mobile app for planning tasks for the day with multimodule architecture, MVI, Compose, Room, Voyager, AlarmManager, Notification, Charts

Language: Kotlin - Size: 413 MB - Last synced at: 20 days ago - Pushed at: 25 days ago - Stars: 514 - Forks: 52

AutoViML/featurewiz_polars

New Polars implementation of the classic featurewiz MRMR algorithm. Created by Ram Seshadri. Collaborators welcome.

Language: Python - Size: 660 KB - Last synced at: 7 days ago - Pushed at: about 1 month ago - Stars: 25 - Forks: 1

surendiran-20cl/Credit_Score_Classification

Developed a multiclass classification system using supervised learning to predict credit score tiers from financial data. Applied EDA, feature engineering, hyperparameter tuning, and evaluated models using ROC-AUC, confusion matrices, and feature importance.

Language: Jupyter Notebook - Size: 1010 KB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 0 - Forks: 0

brenden-DS/Coffee_Shop_Performance_Analysis

Language: Jupyter Notebook - Size: 20.4 MB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 0 - Forks: 0

xinglab-ai/mda

Revealing Hidden Patterns in Deep Neural Network Feature Space Continuum via Manifold Learning (Nature Communications, 2023)

Language: Python - Size: 1.19 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 25 - Forks: 1

firmai/deltapy

DeltaPy - Tabular Data Augmentation (by @firmai)

Language: Jupyter Notebook - Size: 1.47 MB - Last synced at: 4 days ago - Pushed at: over 1 year ago - Stars: 543 - Forks: 55

oskar-j/awesome-auto-ml

Awesome list of AutoML frameworks - curated by @oskar-j

Size: 25.4 KB - Last synced at: 4 days ago - Pushed at: about 2 years ago - Stars: 26 - Forks: 8

sanspareilsmyn/FeatureLens

Real-time Go monitor for ML feature pipeline quality & drift detection

Language: Go - Size: 53.7 KB - Last synced at: 18 days ago - Pushed at: 27 days ago - Stars: 4 - Forks: 1

yzkang/My-Data-Competition-Experience

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

Language: Python - Size: 27.6 MB - Last synced at: 13 days ago - Pushed at: about 4 years ago - Stars: 393 - Forks: 68

saifalibaig/Multi-Label-Emotion-Recognition

This project focuses on detecting multiple emotions from English text using a fine-tuned **BERT** model. It leverages the [GoEmotions](https://huggingface.co/datasets/go_emotions) dataset — a large-scale human-annotated dataset of Reddit comments labeled with 27 emotions + neutral.

Language: Jupyter Notebook - Size: 122 KB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 0 - Forks: 0

HunterMcGushion/hyperparameter_hunter

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Language: Python - Size: 7.27 MB - Last synced at: 14 days ago - Pushed at: over 4 years ago - Stars: 706 - Forks: 101

ajayarunachalam/msda

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Language: Jupyter Notebook - Size: 11.5 MB - Last synced at: 9 days ago - Pushed at: over 3 years ago - Stars: 130 - Forks: 30

Ananyaearth/Image-Processing-and-Computer-Vision

Hands-on notebooks covering image processing & computer vision basics to advanced techniques using Python – filtering, segmentation, HOG, SIFT & more!

Language: Jupyter Notebook - Size: 46.6 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 0 - Forks: 0

somjit101/Human-Activity-Recognition

This project is to build a model that predicts the human activities such as Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing or Laying using readings from the sensors on a smartphone carried by the user.

Language: Jupyter Notebook - Size: 58.2 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 1 - Forks: 0

apachecn/fe4ml-zh

:book: [译] 面向机器学习的特征工程

Language: JavaScript - Size: 14.6 MB - Last synced at: 27 days ago - Pushed at: over 1 year ago - Stars: 2,520 - Forks: 678

SunnyRao07/stroke-risk-prediction

Predicting stroke risk using machine learning models based on healthcare and demographic data.

Language: Jupyter Notebook - Size: 1.63 MB - Last synced at: 25 days ago - Pushed at: 27 days ago - Stars: 0 - Forks: 0

davutbayik/food-delivery-time-prediction

Food Delivery Time Prediction using Machine Learning Techniques

Language: Jupyter Notebook - Size: 47.3 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 2 - Forks: 2

medoidai/skrobot

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

Language: Python - Size: 47.2 MB - Last synced at: 14 days ago - Pushed at: 8 months ago - Stars: 24 - Forks: 2

TimKong21/Medical-Appointment-No-Show-Prediction

A machine learning solution predicting patient no-shows in healthcare appointments. This project integrates EDA, data processing, feature engineering, and XGBoost modeling, with a workflow spanning from Snowflake data retrieval to AWS deployment (S3, SageMaker, Lambda, API Gateway), aiming to enhance appointment management in medical ERP systems.

Language: Jupyter Notebook - Size: 35.4 MB - Last synced at: 4 days ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 0

18520339/san-francisco-crime-classification

Phân tích thăm dò và phân loại tội phạm ở San Francisco

Language: Jupyter Notebook - Size: 34 MB - Last synced at: 2 days ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

RenatoMaynard/Supervised-Machine-Learning-Models-Pytorch-Sklearn

This repository provides a comprehensive implementation of supervised machine learning models using PyTorch and Scikit-learn. It includes end-to-end workflows for both classification and regression tasks, covering data preprocessing, model training, evaluation, and comparison between traditional ML models

Size: 1.95 KB - Last synced at: 2 days ago - Pushed at: about 1 month ago - Stars: 5 - Forks: 0

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 Notebook - Size: 1.26 MB - Last synced at: 28 days ago - Pushed at: 11 months ago - Stars: 702 - Forks: 262

ArunabhaPani/House_price_prediction_kaggle_learning

started by analysing and determining the aspects required for tuning of the final ml model. Performed Eda and feature engineering inorder to determine the import parameters of the dataset and to derive more useful features, finally creating a ml model by using various different basic and advanced regression techniques.

Language: Jupyter Notebook - Size: 1.74 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 0

ArunabhaPani/kaggle_house_price_prediction_advanced_regression_ml_model

started by analysing and determining the aspects required for tuning of the final ml model. Performed Eda and feature engineering inorder to determine the import parameters of the dataset and to derive more useful features, finally creating a ml model by using various different basic and advanced regression techniques.

Language: Jupyter Notebook - Size: 1.69 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 0

joseph-ishola/Movie-Recommendation-Model

Language: Jupyter Notebook - Size: 14.9 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 0

Deanw123outlook/Machine-Learning-Projects

This repository will include feature engineering (dimensionality reduction | data pre-processing techniques) along with popular Supervised and Unsupervised Machine Learning Models !

Language: Jupyter Notebook - Size: 586 KB - Last synced at: 30 days ago - Pushed at: 30 days ago - Stars: 1 - Forks: 0

AutoViML/featurewiz

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.

Language: Python - Size: 10.6 MB - Last synced at: 28 days ago - Pushed at: 3 months ago - Stars: 638 - Forks: 95

shallowManica/Kaggle-Survey-Salary-Prediction

This project builds an ML pipeline to predict Kaggle survey salary buckets. It includes missing value imputation, encoding (OneHot, ordinal, label), feature selection via RandomForestClassifier, and ordinal logistic regression (one-vs-rest) with GridSearchCV tuning, evaluated using accuracy and F1-score.

Language: Jupyter Notebook - Size: 1.69 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Visualize-ML/Book6_First-Course-in-Data-Science

Book_6_《数据有道》 | 鸢尾花书：从加减乘除到机器学习；欢迎大家批评指正！纠错多的同学会得到赠书感谢！

Language: Jupyter Notebook - Size: 169 MB - Last synced at: 29 days ago - Pushed at: 8 months ago - Stars: 2,292 - Forks: 428

sushant1827/Machine-Learning-for-Predictive-Maintenance

Demonstrate the application of machine learning on a real-world predictive maintenance dataset, using measurements from actual industrial equipment.

Language: Jupyter Notebook - Size: 1.67 MB - Last synced at: 29 days ago - Pushed at: 4 months ago - Stars: 3 - Forks: 0

person699/kagglejanestreet

A repository for Kaggle competition code related to Janestreet - a platform for automated trading by market professionals. Contains scripts, notebooks, and models for predicting financial market trends and optimizing trading strategies.

Size: 1000 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 2 - Forks: 0

kknani24/Real-estate-price-prediction

This project builds a state-of-the-art machine learning model for predicting real estate prices. It leverages advanced data preprocessing, feature engineering, and visualization techniques to optimize for accuracy and interpretability.

Language: Jupyter Notebook - Size: 30.3 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

guangyizhangbci/EEG_Riemannian

IEEE Transactions on Emerging Topics in Computational Intelligence

Language: Python - Size: 1.55 MB - Last synced at: 29 days ago - Pushed at: over 1 year ago - Stars: 65 - Forks: 11

mkhekare/heart_ml

Predict the 10-year risk of coronary heart disease (CHD) using patient data from the Framingham Heart Study. The dataset contains over 4,240 records with 15 attributes, allowing for exploration, feature engineering, and the development of classification models

Language: Jupyter Notebook - Size: 362 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

metarank/metarank

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Language: Scala - Size: 23.6 MB - Last synced at: 30 days ago - Pushed at: 4 months ago - Stars: 2,119 - Forks: 92

Aura-healthcare/hrv-analysis

Package for Heart Rate Variability analysis in Python

Language: Python - Size: 8.97 MB - Last synced at: about 1 month ago - Pushed at: 6 months ago - Stars: 408 - Forks: 99

raptor-ml/raptor

Transform your pythonic research to an artifact that engineers can deploy easily.

Language: Go - Size: 4.55 MB - Last synced at: 3 days ago - Pushed at: about 2 months ago - Stars: 153 - Forks: 12

maheshvarade/Mobile-Price-Classification-using-ML-SVM-Logistic-Regression-

This project tackles the challenge faced by a new mobile company founded by Prabhat, who wants to compete with tech giants like Apple and Samsung. The goal is to predict the price range of a mobile phone based on its features — not the exact price, but whether it's low, medium, high, or very high cost.

Language: Jupyter Notebook - Size: 207 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

n-Baiersdorf/LatentMol

LatentMol: a deep molecular representation learning project with custom input format

Language: Python - Size: 626 KB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0

vinta/albedo

A recommender system for discovering GitHub repos, built with Apache Spark

Language: Scala - Size: 442 KB - Last synced at: about 1 month ago - Pushed at: almost 5 years ago - Stars: 177 - Forks: 36

UdayasGunasekaran/World-Population-Analysis

This project aims to analyze global population trends using historical data and predict future growth. Machine learning techniques will be applied to explore demographic data, identify key factors influencing changes, and build predictive models in Python.

Language: Jupyter Notebook - Size: 1.06 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

BBVA/mercury-dataschema

Utility package that, given a Pandas DataFrame, it uses the DataSchema class which auto-infers feature types and automatically calculates different statistics depending on the types.

Language: Python - Size: 645 KB - Last synced at: 28 days ago - Pushed at: 3 months ago - Stars: 15 - Forks: 1

LastAncientOne/Deep_Learning_Machine_Learning_Stock

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Language: Jupyter Notebook - Size: 18.9 MB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 1,362 - Forks: 330

rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy

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

Language: Jupyter Notebook - Size: 83.6 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 2,019 - Forks: 673

brprojects/Energy-Prediction-ML

Predicted Spanish day-ahead energy demand and price with 97.5% accuracy using a range of ML and statistical time series forecasting models including XGBoost, Transformers, TFTs and SARIMA.

Language: Jupyter Notebook - Size: 52.5 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

fatimagulomova/iu-projects

IU Projects

Language: Jupyter Notebook - Size: 127 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

fuqiuai/sklearn-feature-engineering

使用sklearn做特征工程

Language: Python - Size: 29.3 KB - Last synced at: about 1 month ago - Pushed at: almost 7 years ago - Stars: 171 - Forks: 70

ClimbsRocks/auto_ml

[UNMAINTAINED] Automated machine learning for analytics & production

Language: Python - Size: 1.38 MB - Last synced at: 27 days ago - Pushed at: about 4 years ago - Stars: 1,644 - Forks: 312

amzn/rheoceros

Cloud-based AI / ML workflow and data application development framework

Language: Python - Size: 2.49 MB - Last synced at: 12 days ago - Pushed at: 9 months ago - Stars: 17 - Forks: 9

Yimeng-Zhang/Machine-Learning-From-Scratch

系统梳理机器学习的各个知识点。

Size: 44.4 MB - Last synced at: 26 days ago - Pushed at: over 6 years ago - Stars: 122 - Forks: 31

yashsinghrawat/ipl-win-prediction

IPL Win Prediction Project

Language: Jupyter Notebook - Size: 1.25 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

ThomasBury/arfs

All Relevant Feature Selection

Language: Python - Size: 77.6 MB - Last synced at: 29 days ago - Pushed at: about 1 month ago - Stars: 131 - Forks: 14

logicalclocks/hopsworks

Hopsworks - Data-Intensive AI platform with a Feature Store

Language: Java - Size: 152 MB - Last synced at: 29 days ago - Pushed at: 3 months ago - Stars: 1,219 - Forks: 150

Daniel-Andarge/AiML-financial-fraud-detection-model

The Fraud Detection project aims to improve identification of fraudulent activities in e-commerce and banking by developing advanced machine learning models that analyze transaction data, employ feature engineering, and implement real-time monitoring for high accuracy fraud detection.

Language: Jupyter Notebook - Size: 7.7 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 3 - Forks: 2

Daniel-Andarge/AiML-smart-sale-data-driven-store-promotion-analysis-and-retail-forecasting

This project represents a strategic initiative for Rossmann Pharmaceuticals, with the potential to significantly enhance the company's overall performance and competitiveness in the market.

Language: Jupyter Notebook - Size: 13.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

rubydamodar/Loan-approval-prediction-

Loan approval prediction is a popular machine learning project, especially in the banking and finance industry. The goal of this project is to build a predictive model that can determine whether a loan application will be approved or not based on the applicant's information such as income, credit history, and loan amount.

Language: Jupyter Notebook - Size: 2.32 MB - Last synced at: 29 days ago - Pushed at: 6 months ago - Stars: 21 - Forks: 0

who-else-but-arjun/Convolve

This repository contains the projects developed for the Convolve PAN IIT AI-ML Hackathon, conducted by IDFC Bank. Predicting Credit Card Defaulters – A deep learning-based model to assess the risk of credit card default. Optimizing Email Engagement Time Slots – A machine learning model to determine the best time slots for personalised emails.

Language: Jupyter Notebook - Size: 7.19 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 0 - Forks: 1

Subhash-777/Cross-Domain-transfer-learning-from-Human-Motion-to-Robot-Fault-Detection

The code trains an LSTM-based residual model on human motion data and applies transfer learning to detect robotic joint faults. It preprocesses data, maps robot features to human-like patterns, and fine-tunes a model while freezing early layers. The optimized model is evaluated with class weighting, callbacks, and feature importance analysis.

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