bessBest Subset Selection algorithm for Regression, Classification, Count, Survival analysis
Stars: ✭ 14 (-87.39%)
featurewizUse advanced feature engineering strategies and select best features from your data set with a single line of code.
Stars: ✭ 229 (+106.31%)
skrobotskrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Stars: ✭ 22 (-80.18%)
ShapML.jlA Julia package for interpretable machine learning with stochastic Shapley values
Stars: ✭ 63 (-43.24%)
NVTabularNVTabular 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.
Stars: ✭ 797 (+618.02%)
FIFA-2019-AnalysisThis is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
Stars: ✭ 28 (-74.77%)
msdaLibrary 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
Stars: ✭ 80 (-27.93%)
50-days-of-Statistics-for-Data-ScienceThis repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.
Stars: ✭ 19 (-82.88%)
exemplary-ml-pipelineExemplary, annotated machine learning pipeline for any tabular data problem.
Stars: ✭ 23 (-79.28%)
srqmAn introductory statistics course for social scientists, using Stata
Stars: ✭ 43 (-61.26%)
Market-Mix-ModelingMarket Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
Stars: ✭ 31 (-72.07%)
feature engineFeature engineering package with sklearn like functionality
Stars: ✭ 758 (+582.88%)
sparserega collection of modern sparse (regularized) linear regression algorithms.
Stars: ✭ 55 (-50.45%)
broomExtraHelpers for regression analyses using `{broom}` & `{easystats}` packages 📈 🔍
Stars: ✭ 45 (-59.46%)
AutoTSAutomated Time Series Forecasting
Stars: ✭ 665 (+499.1%)
pyspark-ML-in-ColabPyspark in Google Colab: A simple machine learning (Linear Regression) model
Stars: ✭ 32 (-71.17%)
kaggle-berlinMaterial of the Kaggle Berlin meetup group!
Stars: ✭ 36 (-67.57%)
Statistical-Learning-using-RThis is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
Stars: ✭ 27 (-75.68%)
joineRMLR package for fitting joint models to time-to-event data and multivariate longitudinal data
Stars: ✭ 24 (-78.38%)
Trajectory-Analysis-and-Classification-in-Python-Pandas-and-Scikit-LearnFormed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…
Stars: ✭ 41 (-63.06%)
clinkClink is a library that provides APIs and infrastructure to facilitate the development of parallelizable feature engineering operators that can be used in both C++ and Java runtime.
Stars: ✭ 24 (-78.38%)
regression-wasmTesting doing basic regression with web assembly
Stars: ✭ 32 (-71.17%)
GDLibraryMatlab library for gradient descent algorithms: Version 1.0.1
Stars: ✭ 50 (-54.95%)
fengfeng - feature engineering for machine-learning champions
Stars: ✭ 27 (-75.68%)
hierarchical-dnn-interpretationsUsing / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Stars: ✭ 110 (-0.9%)
RegressionMultiple Regression Package for PHP
Stars: ✭ 88 (-20.72%)
Sales-PredictionIn depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.
Stars: ✭ 56 (-49.55%)
gold-price-analysisCreating a model to analyze and predict the trend of the prices of gold.
Stars: ✭ 31 (-72.07%)
machine learning courseArtificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)
Stars: ✭ 47 (-57.66%)
L0LearnEfficient Algorithms for L0 Regularized Learning
Stars: ✭ 74 (-33.33%)
regression-pythonIn this repository you can find many different, small, projects which demonstrate regression techniques using python programming language
Stars: ✭ 15 (-86.49%)
zcaZCA whitening in python
Stars: ✭ 29 (-73.87%)
mrmrmRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
Stars: ✭ 170 (+53.15%)
AIML-ProjectsProjects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
Stars: ✭ 85 (-23.42%)
bbaiSet model hyperparameters using deterministic, exact algorithms.
Stars: ✭ 19 (-82.88%)
BallStatistical Inference and Sure Independence Screening via Ball Statistics
Stars: ✭ 22 (-80.18%)
Data-ScienceUsing Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.
Stars: ✭ 15 (-86.49%)
isarn-sketches-sparkRoutines and data structures for using isarn-sketches idiomatically in Apache Spark
Stars: ✭ 28 (-74.77%)
anovosAnovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Stars: ✭ 77 (-30.63%)
theedhum-nandrumA sentiment classifier on mixed language (and mixed script) reviews in Tamil, Malayalam and English
Stars: ✭ 16 (-85.59%)
EvolutionaryForestAn open source python library for automated feature engineering based on Genetic Programming
Stars: ✭ 56 (-49.55%)
fsfcFeature Selection for Clustering
Stars: ✭ 80 (-27.93%)
Machine-Learning-ModelsIn This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
Stars: ✭ 30 (-72.97%)
tsflexFlexible time series feature extraction & processing
Stars: ✭ 252 (+127.03%)
Python-AndrewNgMLPython implementation of Andrew Ng's ML course projects
Stars: ✭ 24 (-78.38%)
PubMed-Best-MatchMachine-learning based pipeline relying on LambdaMART currently used in PubMed for relevance (Best Match) searches
Stars: ✭ 36 (-67.57%)
MlrMachine Learning in R
Stars: ✭ 1,542 (+1289.19%)
pycobrapython library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.
Stars: ✭ 111 (+0%)
deep-explanation-penalizationCode for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
Stars: ✭ 110 (-0.9%)