Deep learning using CNN in tensorflow on Kaggle image dataset containing 87,900 different healthy and unhealthy crop leaves spanning 38 unique classes.

A novel architecture for enhancing image classification. Reference paper: https://arxiv.org/abs/2104.12294

Using deep learning and transfer learning techniques to differentiate plain roads and those with potholes using three different classifiers to obtain the best accuracy with the same convolutional base

We build a chatbot by implementing machine learning and natural language processing.

Tutorial to show how to extract object localization

Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.

Given an image of a dog, our algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.

Urdu Music Genre Classification using Convolution Neural Networks and Transfer Learning.

Custom Efficient Neural Network For Histopathological Lung Cancer Classification

A supermarket chain called Good Seed wanted to see if Data Science could help them comply with the law by ensuring that they did not sell age-restricted products to underage customers. My task was to build and evaluate a model to verify a person's age.

DermaStratif classifies skin lesion images into 8 disease categories using EfficientNet-B0 with advanced fine-tuning techniques like Base Training, Adapter Fine-Tuning, and LoRA Fine-Tuning. The project includes a Flask app for real-time predictions with detailed disease information.

Transferring MobileNetV2's feature extractor layers to classify flower images.