Using modanet fashion dataset, the clothes images were classified under 5 season (summer,winter,spring,autumn,all).

Combine Python with machine learning principles to discover hidden patterns in raw data

Puthon 3 with already compiled OpenCV, SimpleCV, TensorFlow, Kera, Scikit-image & learn and many more libraries

Implementation of the model "sketch-RNN" by google for generating sketches with a variational auto encoder

Using CNN to recognize indoor scenes. Dataset: MIT Indoor 67

Fruitify is a charming fruit recognition project that harnesses the power of TensorFlow, an advanced machine learning framework.

Image classification with Keras and Tensorflow

How to build, train, and evaluate a Generative Adversarial Network (GAN) for generating fashion images. The project covers all essential steps, from model building to training and evaluation.

Stock Price Predictor App: A machine learning-powered application built with Streamlit to analyze historical stock data, visualize trends (e.g., moving averages), and predict future stock prices using an LSTM model. It fetches real-time data via Yahoo Finance and provides interactive visualizations for informed decision-making.

Train a model from a dataset for predicting cat and dog from image.

Condutional gan for generating images from sketch

comparison of different machine learning models such as GB, XGB and NN to see which performs better at real time SYN flood detection

Image Classifier using CIFAR-10 and TensorFlow/Keras

Developed a working prototype of a University Security Monitoring System using Deep Learning to assist Reva University in maintaining a database of known and unknown persons entering through the entrance gate by detecting the frontal faces of students.

Tuberculosis Vision Scan is an AI-driven tool for detecting tuberculosis from chest X-rays using a fine-tuned VGG16 model with 93.5% accuracy. The project integrates MLOps tools like MLflow, DVC, and AWS CI/CD for efficient model tracking and deployment. A Flask web app allows users to upload X-ray images and receive real-time TB detection results

The project is a neural network-based fashion recommendation system built using Python. The model used for this system is Resnet50, which is a deep learning model used for image recognition. The data used for training the model is scraped from Flipkart, with a total of 65,000 images.

Next-word prediction implemented using a GPT-like transformer decoder-only architecture, integrated with a Streamlit UI for interactive demonstrations.