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hritvikgupta/README.md

Hi there πŸ‘‹, my name is Hritvik

Currenlty Using Following tools for the development apart from my skills:

Power BI Tableau Excel Python TensorFlow PyTorch Jupyter NLP NLTK scikit_learn Java Spring Springboot JavaScript SQL IntelliJ IDEA Postman Kubernetes HTML CSS Mysql Git VS CODE GitHub AWS TypeScript React

Who am I?

  • Name: Hritvik Gupta
  • Programming Skills: Proficient in Python, JavaScript, Java, and C++.
  • Data Analyst: Proficient in excel, Power Bi and Exploratory data analysis using python frameworks using Pandas numpy and matplot
  • Machine Learning Expertise: Strong proficiency in ML frameworks like TensorFlow and PyTorch; knowledgeable in ML libraries such as scikit-learn and NLTK.
  • Research Experience: Built social media chatbots, Conducted LLM research with Transformer algorithms, improving text coherence, achieving 30% enhanced accuracy at University of california, riverside and Conducted a year-long research project at IIT Roorkee, India, focusing on the classification of brain signals under stress.
  • Publication: Co-authored a paper in the IEEE Journal as part of the research at IIT Roorkee, 2 Other publications in NLP.
  • Project Highlights:
    • Developed Interactive Dashboard for companies insightful data such as Sales, Customer retention and Risk analysis.
    • Specialized in MLOps, Mlfow, AWS, GCP, Natural Language Processing and Deep Neural Networks.
    • Recent project at UC Riverside on ensemble neural networks using T5 and LDA for text summarization, leading to a research paper.
  • Additional Publications: Authored several papers in IEEE, primarily on NLP and NLU with a focus on text summarization.

Education

  • πŸŽ“ I have finished my master's in Computer Engineering from University Of California, Riverside : GPA 3.7 | graduated: December 2023.

  • πŸŽ“ I have finished my Bachelor of Technology in Computer Science and Engineering from GITS Udaipur, India : GPA 3.9 | graduated: May 2022.

Current Focus

  • πŸ”­ I’m currently working on with Cognizant as a Data analayst.
  • 🌱 I’m currently learning Kubernetes, Yaml
  • πŸ‘― I’m looking to collaborate on Open Source Projects in NLP and React
  • πŸ’¬ Ask me about NLP Machine Learning Statistics React.js, Redux, Node.js, Express.js
  • πŸ“« How to reach me: hritvik7654@gmail.com
  • πŸ“„ You can check my Resume here

Fun Fact πŸ˜„:

You only need Stack Overflow to be a software developer!

Languages and Tools:

JavaScript React.js Redux Tensorflow Jest Jetpack Compose Room Java Kotlin Python




Android Studio Tensorflow React Native Ionic Xamarin Flutter Swift Visual Studio Code GitHub IntelliJ IDEA Xcode Jupyter



Projects:

1.End-to-End Machine Learning Application on AWS and Digital Ocean: Designed pneumonia detection model with ResNet and computer vision, achieving 95% accuracy on given dataset. Employed AWS SageMaker, S3, Lambda, and API Gateway for streamlined ML operations and model deployment. Developed Next.js web app with Node.js, Express, MongoDB on Digital Ocean, integrated AWS endpoints.

2.Personalised GPT: Streamlit-Based Application Developed Streamlit app with LLMs and vector database for resume QA, achieving 70% better query efficiency. Integrated advanced ML techniques like vector databases and LLM fine-tuning with HuggingFace, Langchain. Deployed Docker container on AWS Lambda for application scalability, achieving a 25% faster deployment times.

3.Flu Trend Analysis via PySpark and GeoPandas Built a user-friendly web interface powered by Tableau, enabling intuitive exploration and analysis of flu trends. Scaled flu trend analysis by 80% data granularity with PySpark GeoPandas, pre-processed on Apache Hadoop. Leveraged AWS S3-stored flu data to train an ARIMA model for California, generating informative heatmaps.

4.Image Captioning: Applied transfer learning with ResNet-50 and custom BiLSTM, boosting caption accuracy by 70% for 100K images. Enhanced image recognition accuracy by 85% using Adam optimizer with pyramid learning rate and cross-validation. Deployed BiLSTM attention model on optimized AWS data pipelines, achieving 15% faster training. Technologies: Keras, NLTK, ResNet-50, LSTM.

5.Text Summarization Using Elmo Embedding: Developed an ensemble algorithm integrating unsupervised embeddings, enhancing analytical precision. Synergized ELmo embedding with supervised cosine similarity, improving summary quality by over 65%. Outperformed previous benchmarks with 8% and 6% hikes in ROUGE-1 and ROUGE-L scores, respectively. Technologies: Tensorflow, NLTK, Attention, LSTM.

6.Dall-E Open AI Text-To-Image Generation Appication: Developed a OpenAI product Dall-e using Tailwind CSS; achieved Β‘2s load time on Netlify deployment. Used ReactJS with Vite environments to design application and achieve 90% uptime, ensuring a seamless software development lifecycle with Render infrastructure.Built a reliable REST API using Node.js and Express.js for efficient data management using MongoDB.

7.E-Commerce Appication: Improved product UI efficiency by 30% using React.js; deployed on Netlify, resulting in a 15% user engagement increase (Google Analytics). Integrated REST API using Redux, Node.js, and Postgres; to support concurrent users monitored via New Relic. Boosted CRUD response times by 20%, reducing request time through middleware optimization (Postman).

8.Note Taking App: Developed an Android app that allows users to create, edit, and manage notes with added features of tagging, priority, and search function, using Kotlin, MVVM architecture, Room for local storage, and Material Design for UI/UX.

9.Shoe E-commerce Store: Built a full-stack e-commerce store with features like user registration, adding to cart, and payment gateway using React, Node.js, Express.js, and MongoDB.

10.To-Do-List-AppHere's the final part: Created a task management app by utilizing Kotlin, HILT, and Room within an MVC framework to build an application with sharing, reminders, attachments, social logins (Google/Facebook), and local storage. Published on Google Play.

Open Source Contributions πŸ‘¨β€πŸ’»:

1.Travel: Developed a responsive Maps web app with map rendering functionality using React and Bootstrap to find live attractions in various global locations. Integrated Google Maps, utilized RapidAPI with Axios for 40% faster API handling, enhancing location services.

2.Shoe-ecom-store: Implemented net banking options in the payment portal of an e-commerce shoe store using React and TypeScript. This addition enhanced customer payment flexibility, allowing UPI Transactions.

3.React To-do App: Worked on a code base of a user-friendly to-do list application integrating Firebase Authentication for secure user login using Redux and Framer Motion.

Extra-curricular Activities 🎯:

  1. Published 3 research papers on Natural Language Processing and EEG in IEEE Journal Google Scholar
  2. Actively reviewing and debugging code in various GitHub repositories as an open-source contributor.
  3. Conveying valuable insights and detailed information through engaging and well-researched blogs.

Portfolio πŸ“«:

visit my website.

Connect with me:

Gmail Linkedin Linkedin




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  1. EEG-DURING-MENTAL-ARTHMETIC-TASK EEG-DURING-MENTAL-ARTHMETIC-TASK Public

    RESEARCH PROJECT, AIM IS TO CLASSIFY THE EEG SIGNALS DURING THE REST STATE AND MENTAL ARITHMETIC TASK STATE

    Jupyter Notebook 1

  2. Image-captioning Image-captioning Public

    Scene understanding, which blends computer vision with natural language processing skills, includes image caption, which automatically generates natural language descriptions based on the content o…

    Jupyter Notebook 1

  3. Docs_classification Docs_classification Public

    This Is NLP base Text Document Classifier Application which first converts the image into text using OCR and then classify it among different sets of classes that text is based upon

    Python

  4. Chatbot Chatbot Public

    ChatBot is the Application of the Natural Language Processing which Trains Neural Networks to produce natural Spoken language.

    Jupyter Notebook 1