This project is about to classify if an event is terrorist or other forms of crime as per the Global Standards.

Implementation of various machine learning algorithms from scratch.

Ensemble methods is a machine learning technique that combines several base models in order to produce one optimal predictive model. To better understand this definition lets take a step back into ultimate goal of machine learning and model building. This is going to make more sense as I dive into specific examples and why Ensemble methods are u…

In This Repository you can find The Explanation and The Implementation of the Most Famous Machine Learning Algorithms

Using DCGAN and Ensemble Learning to classify the difference of the disease of different mangoes.

Face detection (class and pose) using various Classifiers - Own Implementation

From scratch Implementation and analysis of the algorithm Adaboost.

Ensemble Learning Tutorial

Created AdaBoost Model to predict whether the income is <=50K or >50K of an individual. In order to find potential donors.

Classification of Gamma and Hadron events by training classifieres and machine learning algorithms on the MAGIC Gamma Telescope dataset.

Using Various Regression Algorithms to Predict House Sales

Perceptron Implementation - implementing Empirical Risk Minimization (ERM) and k-folds cross-validation

Solution to the (MBTI) Myers-Briggs Personality Type Dataset on Kaggle

Scratch code for a machine learning algorithm involves writing code from scratch to implement the algorithm rather than using pre-built libraries or frameworks.

This project uses machine learning to predict the price of a used car. The model is trained on a dataset of historical car sales data, and it can then be used to predict the price of a car based on its features.

A Project to leverage machine learning algorithms to predict the potential donors based on a number of features.

Using Decision Tree and AdaBoost to classify languages(English/Dutch)

A token is created to invest in long term volatility, which is very profitable in market crisis, but also in bull markets through algorithmic trading using an Adaboost machine learning model and VIXM.

Sétimo mini projeto de data science em que pude usar diversos modelos de regressão para prever o preço das casas a partir de um conjunto diversificado de features

Implementation of several ML models like decision tree, linear regression, ensemble methods, etc.