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Feature Engineering And Feature Selection ⭐ 798

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Amazing Feature Engineering ⭐ 485

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.

Deltapy ⭐ 411

DeltaPy - Tabular Data Augmentation (by @firmai)

Feature Engineering For Machine Learning ⭐ 314

Code repository for the online course Feature Engineering for Machine Learning

Nlpython ⭐ 302

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"

Ego4d dataset repository. Download the dataset, visualize, extract features & example usage of the dataset

Python_computer_vision_from_scratch ⭐ 219

This repository explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

The Building Data Genome Project ⭐ 140

A collection of non-residential buildings for performance analysis and algorithm benchmarking

Bertqa Attention On Steroids ⭐ 105

BertQA - Attention on Steroids

Alexnet Experiments Keras ⭐ 101

Code examples for training AlexNet using Keras and Theano

⏳ ChatLog: Recording and Analysing ChatGPT Across Time

Nba_betting ⭐ 93

Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.

Visual Similarity research at Fynd. Contains code to reproduce 2 of our research papers.

Fedot.industrial ⭐ 62

Python framework for automated time series classification, object recognition and anomaly detection

Lane And Vehicles Detection ⭐ 53

This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, IIT Bombay.

Python Implementation of Feature Extraction with K-Nearest Neighbor

Mlnotebooks ⭐ 52

Demonstration notebooks for Machine Learning

Dalf_cvpr_2023 ⭐ 46

DALF is a joint image keypoint detector and descriptor for handling non-rigid deformations. It also works great under large rotations.

Emotion Recognition ToolKit (ERTK): tools for emotion recognition. Dataset processing, feature extraction, experiments,

Machine_learning_course ⭐ 44

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

Music Genre Classification ⭐ 37

Automatic Music Genre Classification with Machine Learning Techniques

Iconographic Visualization Inside Computational Notebooks

Eeg Motor Imagery Classification Ann ⭐ 33

Classification of BCI competition VI dataset 2a using ANN by applying WPD and CSP for feature extraction

Graph Representation Analysis for Connected Embeddings

Subject-wise networks from structural MRI, both vertex- and voxel-wise features (thickness, GM density, curvature, gyrification)

Pyaesthetics ⭐ 27

A python package to extract visual features about the aesthetic appearance from still images.

Python Sound Tool ⭐ 23

SoundPy (alpha stage) is a research-based python package for speech and sound. Applications include deep-learning, filtering, speech-enhancement, audio augmentation, feature extraction and visualization, dataset and audio file conversion, and beyond.

Graph Stuff ⭐ 21

Things related to graphs

NABNet: A Nested Attention-guided BiConvLSTM Network for a robust ‎prediction of Blood Pressure components from reconstructed Arterial Blood ‎Pressure waveforms using PPG and ECG Signals

Sentimentarcs_notebooks ⭐ 17

SentimentArcs: a large ensemble of dozens of sentiment analysis models to analyze emotion in text over time

Instacart Market Basket Analysis ⭐ 17

The objective of this project is to analyze the 3 million grocery orders from more than 200,000 Instacart users and predict which previously purchased item will be in user's next order. Customer segmentation and affinity analysis are done to study customer purchase patterns and for better product marketing and cross-selling.

Feature Extraction Eeg ⭐ 16

Feature Extraction of Mental Load EEG signals

50 Days Of Statistics For Data Science ⭐ 15

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Biosignal Emotions Bhs 2020 ⭐ 14

Multispectral Feature Descriptor (MFD).

Flight_delay_prediction ⭐ 12

A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

Geobitnonrigiddescriptor_iccv_2019 ⭐ 12

C++ implementation of the nonrigid descriptor Geobit presented at ICCV 2019 "GEOBIT: A Geodesic-Based Binary Descriptor Invariant to Non-Rigid Deformations for RGB-D Images"

Hr Analytics ⭐ 12

Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

Radiomics Research By Using Python ⭐ 12

Radiomics (here mainly means hand-crafted based radiomics) contains data acquire, ROI segmentation, feature extraction, feature selection, machine learning modeling, and stastical analysis.

Natural Language Processing Tutorials ⭐ 12

NLP Webinars Created for Udacity's Mentorship Program (2019).

Big_data_course_rimini_2021 ⭐ 11

Questa repository contiene tutto il materiale didattico utilizzato durante il corso di "Laboratorio Big Data" in collaborazione con il comune di Rimini.

Restaurant Reviews Analysis ⭐ 10

Using Natural Language Processing and Bag of Words for feature extraction for sentiment analysis of the customers visited in the Restaurant and at last using Classification algorithm to separate Positive and Negative Sentiments.

Churn Modelling Dataset ⭐ 10

Predicting which set of the customers are gong to churn out from the organization by looking into some of the important attributes and applying Machine Learning and Deep Learning on it.

CMS data quality monitoring

Cml_amp_image_analysis ⭐ 10

Build a semantic search application with deep learning models.

Deep Learning Gene Expression ⭐ 10

Deep learning methods for feature selection in gene expression autism data.

Humbugdb ⭐ 10

Acoustic mosquito detection code with Bayesian Neural Networks

Computer Vision ⭐ 9

Find the implementation of Computer vision-based projects with Python, Deep Learning, and OpenCV

Data_processing_and_feature_engineering_in_machine_learning ⭐ 9

This is an attempt to summarize feature engineering methods that I have learned over the course of my graduate school.

Water Based Indices On Sentinel 2a Images Using Python ⭐ 9

Satellite Image Processing, Feature Extraction using Python on level 2A Sentinel 2 satellite imagery to enhance water bodies.

Google Job Skills ⭐ 9

Having an Exploratory Analysis at what kind of Jobs and Job Locations are provided by Google and Youtube, also we look into some specific details which are important to get hired by youtube and google.

Hyperspectral Image Classification ⭐ 9

Comparative analysis of different feature extraction techniques for hyperspectral image classification.

Pyconvnetphash ⭐ 9

image perceptual hash experiment using convolutional neural net models

Environmental Sound Classification Esc Using Neural Networks And Other Classifiers ⭐ 8

Audio feature extraction and multi-classification with the ECS-10 data set

Social Networks Ads ⭐ 8

One of the most basic data sets to learn and implement some of the most easy and basic algorithms of machine learning and visualization

Mml Feature Learning ⭐ 8

Miami Machine Learning Meetup - Feature Learning with Matrix Factorization and Neural Networks

Eeg_signalsclassification ⭐ 7

Preprocessing, analysis and classification of EEG signals into 4 classes.

Employee Reviews ⭐ 7

This is Project which contains Data Visualization, EDA, Machine Learning Modelling for Checking the Sentiments.

Avito Demand Prediction Challenge ⭐ 7

It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting

Image Search Using Parallel Computing ⭐ 7

CRISP is a Fast Image Search application that retrieves similar images from a database based on the query image by using Parallel computing paradigm.

Hdl_forensics ⭐ 7

Models for verification and identification of document writers

Xrayimage_extractfeatures ⭐ 7

Extract GLCM, Region Properties, and Moments related features in a line of code and then get those into a data-frame.

Deal_neurips_2021 ⭐ 7

PyTorch implementation of the descriptor DEAL presented at NeurIPS 2021 "Extracting Deformation-Aware Local Features by Learning to Deform".

Tanalysis ⭐ 7

A python 2.7+ and 3.4+ package for matrix product state decompositions in a data science context

Off The Shelf Insect Identification ⭐ 6

Main contribution of this repo is thorough evaluation of off-the-shelf approach for image classification based on a feature extraction with a single feed forward pass trough pretrained VGG16.

Sequence Graph Transform ⭐ 6

Careercon Robots Need Help ⭐ 6

It is Data Science and Machine Learning Competition Hosted by Kaggle where we have to perform multi-class classification on the labels, a very good amount of feature engineering, data preprocessing, data visualizations and modelling is done on the data set to get a good accuracy using random forest and xg boost classifier

Pathcore T Analysis ⭐ 6

This repository is in support of the PathCORE-T paper (https://doi.org/10.1101/147645). It contains all the code and necessary data/metadata to repeat all analyses in the paper.

Electrical Devices Identification Model ⭐ 6

Electrical Devices Identification Model (EDIM) for the identification of electrical devices by analyzing their energy consumption profiles.

Hsi Toolbox ⭐ 6

Hyperspectral CNN compression and band selection

Amazon Alexa Reviews ⭐ 6

Using Natural Language Processing, Data Visualizations and Classification Algorithms of Machine Learning

Disinfo Doppler ⭐ 6

A collection of code to help study images

Udacity Vehicle Detection Project ⭐ 6

Speech To Emotion ⭐ 6

Emotion is an intuitive feeling which can be determined from any person’s circumstances and surroundings. But in this project, we tried to identify the emotional state of a person using his voice as input.

Model Mgmt On Watson Studio Local ⭐ 5

Feature Engineering and Model Deployments using Watson Studio Local

Mlexperiments ⭐ 5

Machine learning model implementations using pytorch, fastai, pytorch-lightning

Avalinguo Dataset Speaker Fluency Level Classification Paper ⭐ 5

Avalinguo Dataset Speaker Fluency Level Classification using Machine Learning Techniques - Paper Replication Data

Speaker Recognition ⭐ 5

Identifying which celebrity is speaking through deep learning

Dimensionality Reduction Pca ⭐ 5

Dimensionality reduction is basically a process of reducing the amount of random features,attributes variables or in this case called dimensions in a dataset and leaving as much variation in the dataset as possible by obtaining a set of only relevant features to increase the effiency of a model.

Telecom Churn Prediction ⭐ 5

Telecom Churn Prediction using Machine Learning models

Rbc Classification Convnet ⭐ 5

Thunder Extraction ⭐ 5

algorithms for feature extraction from spatio-temporal data

Stock Prediction Portfolio Optimization ⭐ 5

A Streamlit based application to predict future Stock Price and pipeline to let anyone train their own multiple Machine Learning models on multiple stocks to generate Buy/Sell signals. This is a WIP and I will keep on adding new ideas to this in future.

Machine Learning ⭐ 5

C++ and Python Codes from my projects

DBFE is a Python library with feature extraction methods that facilitate classifier learning from distributions of genomic variants.

Loan Default Prediction ⭐ 5

L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’. where I have predicted whether the customer will be defaulter in the first EMI payment using different algorithms from machine learning

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