Pinned Repositories
anime-GAN
Fun project for generating anime pictures using Deep Convolutional Generative Adversarial Networks (DCGAN)
careers_website
A career website .
file_manager
gan
Keras-GAN
Keras implementations of Generative Adversarial Networks.
keras-seq2seq-chatbot-with-attention
It is a seq2seq encoder decoder chatbot using keras and with attention
lstm_text_generator
models
Models and examples built with TensorFlow
pygta5
Explorations of Using Python to play Grand Theft Auto 5.
visual_question_answering
kunalkushwahatg's Repositories
kunalkushwahatg/visual_question_answering
kunalkushwahatg/anime-GAN
Fun project for generating anime pictures using Deep Convolutional Generative Adversarial Networks (DCGAN)
kunalkushwahatg/careers_website
A career website .
kunalkushwahatg/file_manager
kunalkushwahatg/gan
kunalkushwahatg/Keras-GAN
Keras implementations of Generative Adversarial Networks.
kunalkushwahatg/keras-seq2seq-chatbot-with-attention
It is a seq2seq encoder decoder chatbot using keras and with attention
kunalkushwahatg/lstm_text_generator
kunalkushwahatg/models
Models and examples built with TensorFlow
kunalkushwahatg/pygta5
Explorations of Using Python to play Grand Theft Auto 5.
kunalkushwahatg/-Cyborg_opencv_2
kunalkushwahatg/cuda-programming-exercises
Explore CUDA programming with exercises, projects, and examples in CUDA C. Learn GPU-accelerated computing techniques for NVIDIA GPUs to enhance parallel computing skills.
kunalkushwahatg/cyborg_notes_app
This Notes App is a user-friendly application built with JavaScript, HTML, and CSS. It allows users to create, edit, and delete notes easily. The notes are stored in the browser's local storage, ensuring that they persist even after the page is refreshed. This app is perfect for anyone who needs a simple, reliable way to keep track of their thought
kunalkushwahatg/dsa
kunalkushwahatg/electronics_component_detection
A custom object detection model powered by YOLO for accurately identifying and classifying electronic components. This project includes a unique dataset generated by overlaying component images on various backgrounds with augmentation, as well as a full training and inference pipeline for streamlined model deployment.
kunalkushwahatg/lang_chain_practice
Contains the the practice files of lang chains.
kunalkushwahatg/lectures
Material for gpu-mode lectures
kunalkushwahatg/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
kunalkushwahatg/low_light_image_enhancement
This FastAPI application is designed to enhance images captured in low light conditions using a pre-trained model. It provides an efficient and easy-to-use API for enhancing the visibility of images suffering from poor lighting.
kunalkushwahatg/ml4e-task-newsapp
kunalkushwahatg/ml_model_trainer
kunalkushwahatg/myshop
kunalkushwahatg/paddy_classification
This repository hosts a dataset for classifying diseases affecting paddy crops, curated for machine learning research and development. The dataset consists of 10,406 high-resolution images of paddy leaves, meticulously categorized into 10 distinct disease classes
kunalkushwahatg/sentiment_analysis_rnn
Contains the implementation of sentiment analysis recurrent neural network model in pytorch .
kunalkushwahatg/TF_Object_Detection2020
A guide on how to setup TensorFlow Object Detection API in 2020
kunalkushwahatg/transformer_from_scratch
Transformer from scratch in pytorch
kunalkushwahatg/voice_assistant
This is the simple voice_assistant and it can be used for simple purposes . My first github repo
kunalkushwahatg/wine_quality
A pytorch based neural network model for regression of wine_quality dataset
kunalkushwahatg/yolov1_from_scratch
YOLOv1 from Scratch is an implementation of the YOLOv1 (You Only Look Once) object detection algorithm using Python. This project aims to provide a clear, concise, and educational implementation of the YOLOv1 paper, allowing users to grasp and experiment with the fundamental concepts
kunalkushwahatg/yolov5
This repository contains a Python script for object detection using YOLOv5. The script utilizes pre-trained YOLOv5 models of different sizes to detect objects such as cars, bicycles, buses, trucks, and motorbikes in images. Detected objects are highlighted with bounding boxes and labeled accordingly.