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1. Unsupervised-ML Unsupervised-ML Public

   Unsupervised Machine Learning techniques (R and Python): CLUSTERING, FACTOR ANALYSIS AND CORRESPONDENCE ANALYSIS

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2. Supervised-ML Supervised-ML Public

   OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Sign…

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3. DeepLearning DeepLearning Public

   Deep Learning concepts and techniques: Regularization, Epochs, Batch,Hyperparameters, Cross validation, Optimizers

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4. BayesianInference BayesianInference Public

   The model predicts the treatment success rate for new TB cases with high accuracy and robustness. Two different approaches: PCA and Bayesian Inference. The Bayesian regression analysis reveals that…

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5. ApacheSystemML ApacheSystemML Public

   The purpose of this repository is to process data , prepare it, and build models to predict certain activities using ML techniques. The entire process leverages PySpark for distributed data process…

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6. Embeddings Embeddings Public

   Embeddings for Flight Price Prediction. The dataset has few variables, being a true challenge to improve the model's performance. Here, we test the quality & robustness of embeddings for categorica…

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