Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python. Opensource analytics, predictive analytics over clickstream, sentiment analysis, AB tests, machine learning, and Monte Carlo Markov Chain simulations, extending Pandas, Networkx and sklearn.

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python machine-learning library data-visualization pandas segmentation machinelearning business-intelligence predictive-modeling web-analytics

Islr Python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

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Jupyter Notebook machine-learning predictive-modeling statistical-learning islr islr-python

ML2017FALL

Machine Learning (EE 5184) in NTU

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Jupyter Notebook machine-learning sentiment-analysis text-classification clustering cnn rnn image-classification recommender-system pm25 predictive-modeling unsupervised-learning sentiment-classification recommendation-algorithm

ZS-Data-Science-Challenge

A Data science challenge - "Mekktronix Sales Forecasting" organised by ZS through Hackerearth platform. Rank: 223 out of 4743.

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Jupyter Notebook python data-science machine-learning-algorithms hackerearth predictive-modeling

fireTS

A python multi-variate time series prediction library working with sklearn

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python machine-learning time-series predictive-modeling time-series-analysis narx time-series-prediction autoregression nonlinear-time-series nonlinear-timeseries-analysis

Market-Mix-Modeling

Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales

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r linear-regression eda data-visualization feature-selection elasticity feature-engineering predictive-modeling data-preparation factor-analysis market-mix-model marketing-levers ecommerce-firm

Recommender-System

In this code we implement and compared Collaborative Filtering algorithm, prediction algorithms such as neighborhood methods, matrix factorization-based ( SVD, PMF, SVD++, NMF), and many others.

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python collaborative-filtering recommender-system predictive-modeling

CAST

Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

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r machine-learning spatial variable-selection feature-selection caret autocorrelation predictive-modeling spatio-temporal overfitting

learnr

Exploratory, Inferential and Predictive data analysis. Feel free to show your ❤️ by giving a star ⭐

✭ 64

r exploratory-data-analysis inferential-statistics predictive-modeling

BAS

BAS R package https://merliseclyde.github.io/BAS/

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c r cran regression variable-selection model-selection bayesian r-package predictive-modeling mcmc

solar-forecasting-RNN

Multi-time-horizon solar forecasting using recurrent neural network

✭ 29

Jupyter Notebook python pytorch solar rnn predictive-modeling renewable-energy solar-forecasting multi-time-horizon

Kaggle

Kaggle Kernels (Python, R, Jupyter Notebooks)

✭ 26

Jupyter Notebook data-science machine-learning exploratory-data-analysis data-visualization kaggle-competition r-markdown xgboost rstats lightgbm r-language predictive-modeling jupyter-notebooks kaggle-dataset covid-19

mljar-api-R

R wrapper for MLJAR API

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r machine-learning machine-learning-api predictive-modeling predictive-analytics prediction-algorithm

ufc fight predictor

UFC bout winner prediction using neural nets.

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HTML python Jupyter Notebook neural-network dash scrapy predictive-modeling

NDD

Drug-Drug Interaction Predicting by Neural Network Using Integrated Similarity

✭ 25

python deep-neural-networks neural-network similarity neural-networks drug-discovery similarity-measures predictive-modeling snf ndd drug-drug-interaction drug-target-interactions drug-similarities

timemachines

Predict time-series with one line of code.

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python timeseries time-series prediction predictions predictive-modeling prediction-algorithm time-series-analysis timeseries-data timeseries-analysis timeseries-forecasting

Statistical-Learning-using-R

This 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.

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r machine-learning-algorithms statistical-learning datascience data-analysis logistic-regression regularization decision-trees predictive-modeling polynomial-regression clustering-algorithm svm-classifier k-nn boosting generalized-additive-models supervised-machine-learning bagging depth-interpretation discriminant-anlaysis

STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDA

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

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Jupyter Notebook python pipeline random-forest prediction stock logistic-regression predictive-analysis stocks adaboost predictive-modeling algorithmic-trading decision-tree svm-classifier quadratic-discriminant-analysis parameter-tuning guassian-processes gridsearchcv knn-classifier

datafsm

Machine Learning Finite State Machine Models from Data with Genetic Algorithms

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r C++machine-learning genetic-algorithm decision-making artificial-intelligence evolutionary-algorithms finite-state-machine game-theory decision-model predictive-modeling fitness-score evolutionary-computation predictor-variables explainable-ai behavioral-game-theory

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