Repository for the Brainhack School 2020 team working with fMRI and ABIDE data to train machine learning models.

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

ML model for stock trend prediction using Python

Implementation scripts of Machine Learning algorithms on Scikit-learn and Keras for complete novice..

Credit Card Fraud Detection Project

Codes and templates for ML algorithms created, modified and optimized in Python and R.

Contains all my data science projects.

No description provided.

This is an algorithm for evenly partitioning.

Classify pictures by architectural style and recognize objects with CNNs and YOLO

Titanic rescue prediction using Decision Tree, SVM, Logistic Regression, Random Forest and KNN. The best accuracy score was from Random Forest: 84.35%

Machine Learning algorithms built from scratch for AMMI Machine Learning course

This repository contains a Python implementation for solving a two-class classification problem using CSP features extracted from EEG data. The classification task involves discriminating between mental tasks, specifically imagining foot movement and performing mental discrimination.

A comprehensive MATLAB-based machine learning project covering data preprocessing, dimensionality reduction, supervised and unsupervised learning algorithms, model evaluation, and validation techniques with practical examples.

Machine learning: Practical applications

Predicting students admission with Logistic Regression, Decision Tree, SVM (SVC) and Random Forest

Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.

[College Course] - Course: BITS F312 Neural Network and Fuzzy Logic

保险反欺诈预测

Optimizing-Hyperparameters-Using-Grid-Search-Deep-Learning

An Artificial Neural Network with weight decay created using python using the Numpy library which can read handwritten digits. Uses K-Folds cross validation for training the Neural Network.

Linear Regression Feature Selection and Trainer

A Baby Sign Live Recognition Model

This project was made for classifying Covid and non-covid patients through cough sound. This is a non-invasive, inexpensive, and easy method so we can use that as the first filter

Collaborative filtering, word Embedding dense vector representation - NeuralNetwork regression model and K-Fold Evaluation.

PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM

Artificial intelligence model that detects intrusions in a network by analyzing TCP / IP packets by machine learning algorithms

Data sampling library

Imagine you are the front runner for democratic party primaries in 2008 - 1 week into elections you have won a few states(Obama) and your opponent (Hillary) is catching up. How you can use analytics to predict which of the remaining seats will you win using demographic data from states you won and lost. Can we accurately classify win or lose for the remaining seats using data. Can we use this prediction to find out factors which impact our chances of winning and improve our appeal to places that are predicted loss thus improving our chances of winning? Well , Let's find out!

Breast cancer classification and evaluation of classifiers