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45 Analytic Techniques Used by Data Scientists

These techniques cover most of what data scientists and related practitioners are using in their daily activities, whether they use solutions offered by a vendor, or whether they design proprietary tools The 45 data science techniques   Linear Regression  Logistic Regression  Jackknife Regression * Density Estimation  Confidence Interval  Test of Hypotheses  Pattern Recognition  Clustering - (aka Unsupervised Learning) Supervised Learning  Time Series  Decision Trees  Random Numbers  Monte-Carlo Simulation  Bayesian Statistics  Naive Bayes  Principal Component Analysis - (PCA) Ensembles  Neural Networks  Support Vector Machine - (SVM) Nearest Neighbors - (k-NN) Feature Selection - (aka Variable Reduction) Indexation / Cataloguing * (Geo-) Spatial Modeling  Recommendation Engine * Search Engine * Attribution Modeling * Collaborative Filtering * Rule System  Linkage Analysis  Association Rules  Scoring Engine  Segmentation  Predictive Modeling  Graphs  Deep Learning  Game Theory  Imputation  Survival Analysis  Arbitrage  Lift Modeling  Yield Optimization Cross-Validation Model Fitting Relevancy Algorithm * Experimental Design

Saurabh Jain

Saurabh Jain

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