This project aims to understand and implement all the cross validation techniques used in Machine Learning.

Classificador vocacional para o mercado de dados brasileiro utilizando o processo KDD, arquitetura modular e modelos de Machine Learning (Random Forest & MLP) sobre o dataset State of Data.

e2e machine learning pipeline using a config based approach for classification problems. Supports grouping and grading classifiers in addition to online learning algorithms

Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking sites - Facebook.

The goal of this project is to develop an automatic classification system for exotic fruits based on numerical features using the K-nearest neighbors (K-NN) algorithm