Collection of RNN GAN SNN CNN in Tensorflow

📔 This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explore model optimization techniques such as confusion matrix, precision, recall, Roc curve and F1 score to effectively mitigate default risks.

These are all of my machine learning codes.You can find every code about machine learning.

Image classification with DeiT model, including data preprocessing, k-fold CV, early stopping and model saving.

A Streamlit ML app for flight price prediction. This one project involves concepts like EDA, Linear, Lasso & Ridge Regression, Kfold, Hyper Parameter Tuning & GridSearchCV. I am constantly building a rich repository of all the information I have on a particular topic as part of my machine learning practice. Very Helpful for ML beginners.

Data sampling library

Data sampling library

Data sampling library

Utility function to plot roc curves using k-fold cross-validation

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.

Implementing an ANN using PyTorch (under 800,000 parameters) to achieve +92% accuracy in under 100 epochs.

Analyzing and predicting life expectancy of a country based on multiple factors using multiple regression techniques

Use of Linear Regression model to predict price of house in Banglore - Supervised Machine learning Approach

Machine Learning with Python

This is an algorithm for evenly partitioning.

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

This repository contains a Machine Learning model that predicts the comprehensive strength of concrete

A Baby Sign Live Recognition Model

Predict math score using these features gender, race/ethnicity, parental level of education, lunch, test preparation course, reading score, writing score.