Himanshu Kumar's Projects
Dining Concierge Chatbot that sends you restaurant suggestions based on a set of preferences that you provide the chatbot with through conversation (AWS).
Implement a machine learning model to predict whether a message is spam or not. Furthermore, you will create a system that upon receipt of an email message, it will automatically flag it as spam or not, based on the prediction obtained from the machine learning model.
Predict the number of bike rentals at any hour of the year given the weather conditions.
CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art
Teach a Quadcopter How to Fly!
MIT S094: Deep Learning for Self-Driving Cars
Keras Notebook Implementations
Deep Neural Networks with Tensorflow (CNNs,RNNs)
Train a recurrent neural network on scripts from The Simpson's (copyright Fox) to generate new scripts.
A convolutional neural network trained to classify dog breeds.
Dog Vs Cats Classification using VGG16
A spam detection system built on AWS cloud, that upon receipt of an email message, automatically flags it as spam or not. This is based on the prediction obtained from the machine learning model created using Amazon SageMaker. The definition and provision of the resources on AWS cloud is done through the AWS Cloudformation template
Electric Vehicle Fleet management system is designed to capture all the important data that might be useful for an automobile center for smooth day to day operation. For example, an automobile needs to keep track of records of the items that need to be traded for both buying and selling.
Use a DCGAN on the CelebA dataset to generate images of novel and realistic human faces.
GitHub Repository Description
Sentiment Analysis with LSTM mini batch process using Tensor Flow
Machine learning algorithm implementations In python and Matlab
MNIST dataset Keras Implementation
Repository for Programming Assignment 2 for R Programming on Coursera
LLM Chatbot with Retrieval Augmented Generation using Llamaindex. It works both in online and offline mode.
This is a question and answer (Q&A) application based on Langchain and Chroma DB, designed to provide answers to questions related to the NYU website.
Sentiment analysis using NLTK Toolkit(Twitter API)