Pinned Repositories
Applied-Deep-Learning-with-Keras
Deep Learning examples with Keras.
ChatBot
This is a Chatbot which uses RAG concept and answers the queries specific the the questions
detr
adscada
DRL_taxi_game
Deep reinforcement learning can be applied to solve the taxi drop game by training a neural network to learn the optimal policy for the taxi agent. The network takes the current state of the game as input and outputs the best action to take. Through trial and error, the agent learns to maximize its cumulative rewards.
GAN_Pytorch
This refers to the implementation of Generative Adversarial Networks (GANs) using the PyTorch library. GANs are deep learning models that consist of two neural networks, a generator and a discriminator, which work in a competitive manner to generate realistic synthetic data.
Hexbug_tracking
This repository refers to building an AI agent to track artificial hexbugs in complex environments
Lime_Images
The main idea of LIME is to approximate the black box machine learning model locally (per sample) using a surrogate model. The surrogate model is a simple interpretable model.
MVViT
Multi-View Transformer based information exchange module
Segformer_for_hexbugs
SegFormer is a simple, efficient yet powerful semantic segmentation framework which unifies Transformers with lightweight multilayer perception (MLP) decoders.
Snowflake_generate
This is a snowflake generator in python. It generates random colors for snowflakes. You can pip install and then play with it.
SalilBhatnagarDE's Repositories
SalilBhatnagarDE/ChatBot
This is a Chatbot which uses RAG concept and answers the queries specific the the questions
SalilBhatnagarDE/Hexbug_tracking
This repository refers to building an AI agent to track artificial hexbugs in complex environments
SalilBhatnagarDE/testing
testing git
SalilBhatnagarDE/Lime_Images
The main idea of LIME is to approximate the black box machine learning model locally (per sample) using a surrogate model. The surrogate model is a simple interpretable model.
SalilBhatnagarDE/VisionTransformers
Vision Transformers are the state of the art methods for classification or object detection problems. Images are divided into patches and then fed into transofmer encoder with positional encodings.
SalilBhatnagarDE/GAN_Pytorch
This refers to the implementation of Generative Adversarial Networks (GANs) using the PyTorch library. GANs are deep learning models that consist of two neural networks, a generator and a discriminator, which work in a competitive manner to generate realistic synthetic data.
SalilBhatnagarDE/detr
adscada
SalilBhatnagarDE/Snowflake_generate
This is a snowflake generator in python. It generates random colors for snowflakes. You can pip install and then play with it.
SalilBhatnagarDE/Segformer_for_hexbugs
SegFormer is a simple, efficient yet powerful semantic segmentation framework which unifies Transformers with lightweight multilayer perception (MLP) decoders.
SalilBhatnagarDE/DRL_taxi_game
Deep reinforcement learning can be applied to solve the taxi drop game by training a neural network to learn the optimal policy for the taxi agent. The network takes the current state of the game as input and outputs the best action to take. Through trial and error, the agent learns to maximize its cumulative rewards.
SalilBhatnagarDE/MVViT
Multi-View Transformer based information exchange module
SalilBhatnagarDE/Applied-Deep-Learning-with-Keras
Deep Learning examples with Keras.