A New, Interactive Approach to Learning Data Science

This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

Nudity/pornography detection using deeplearning. This model is trained using pretrained VGG-16. To know more about this check the readme file below

ML-powered Loan-Marketer Customer Filtering Engine

Designing your first machine learning pipeline with few lines of codes using Orchest. You will learn to preprocess the data, train the machine learning model, and evaluate the results.

Binary Classification of mnist data using Stochastic Gradient Descent(SGD)

A computer vision-based waste identifier utilizes advanced image processing techniques and machine learning

This project demonstrates the implementation of the Perceptron algorithm for binary classification tasks. It includes various advanced features such as data augmentation, feature engineering, and deep learning techniques to enhance model performance and robustness.

PdM for Industrial Equipment using Binary and Multi-Class Classification

This project was built within 24h by the team Augusteam for the DevHacks 2022 Climate Change hackathon sponsored by Systematic and it won the third place worth 500€

DECISION TREE CLASSIFIER - HYPER PARAMETER TUNING - Binary Classification

Develop a technology for detecting mining sites using images from the optical satellite Sentinel-2. Specifically, it involves classifying images that contain mining sites and those that do not.

Implementing a model that can verify if two images belongs to same personality or not. Answer the question "Is this the claimed person?" It is a 1:1 matching problem i.e. given a face your task is to compare the candidate face to another and verify whether it is a match or not. My custom CNN model has achieved marvelous performance on the dataset.

A model for binary classification of credit card data as fraudulent or legitimate

This is heart disease prediction project that contains different methods such as FNN with Multiclass Classification, Binary Classification, Cross-Validation etc.