Himanshu Kumar (hk3427)

hk3427

Geek Repo

Company:New York University

Location:New York, USA

Home Page:https://www.linkedin.com/in/himanshu-kumar-71099a117/

Twitter:@Himanshu_z1

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Himanshu Kumar's repositories

RAG-Langchain-NYUINFO

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.

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hk3427

GitHub Repository Description

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RAG-KnowledgeLLM-LlamaIndex-BOT

LLM Chatbot with Retrieval Augmented Generation using Llamaindex. It works both in online and offline mode.

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EV-Fleet-Management-System

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.

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AWS-Email-Spam-Detection

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.

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Bike-Sharing-Demand-Prediction

Predict the number of bike rentals at any hour of the year given the weather conditions.

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Deep-Traffic

MIT S094: Deep Learning for Self-Driving Cars

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Deep-RL-Quadcopter-Controller

Teach a Quadcopter How to Fly!

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AWS-Dining-Concierge-Chatbot

Dining Concierge Chatbot that sends you restaurant suggestions based on a set of preferences that you provide the chatbot with through conversation (AWS).

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email-spam-detection-aws

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

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Taxi-v1---OpenAI-Gym

This task was introduced in [Dietterich2000] to illustrate some issues in hierarchical reinforcement learning. There are 4 locations (labeled by different letters) and your job is to pick up the passenger at one location and drop him off in another. You receive +20 points for a successful dropoff, and lose 1 point for every timestep it takes. There is also a 10 point penalty for illegal pick-up and drop-off actions.

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Face-Generation-GANs

Use a DCGAN on the CelebA dataset to generate images of novel and realistic human faces.

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DNLD-tv-script-generation

Train a recurrent neural network on scripts from The Simpson's (copyright Fox) to generate new scripts.

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dl-nbs-tensorflow

Deep Neural Networks with Tensorflow (CNNs,RNNs)

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DNLD_Dog-Breed-Classifier

A convolutional neural network trained to classify dog breeds.

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dl-nbs-keras

Keras Notebook Implementations

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CapsNet

CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art

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web-monitoring-processing

Data processing, PageFreezer integration, and (eventually) diff filtering and processing

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mnist-keras

MNIST dataset Keras Implementation

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dogsvsCats-keras-tensorflow-dl

Dog Vs Cats Classification using VGG16

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ProgrammingAssignment2

Repository for Programming Assignment 2 for R Programming on Coursera

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