Skip to content
View rv-harsha's full-sized avatar
🎯
Focusing
🎯
Focusing

Block or report rv-harsha

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
rv-harsha/README.md

About me ..

  • 👋 Hello.
  • 👀 I’m a passionate, curious and self-driven software engineer currently exploring emerging AI technologies.
  • 🌱 It fascainates how software technologies are evolving to solve complex real world challenges. Positvely looking forward to be a part of it.
  • 💞️ I’m looking to collaborate on software applications in WebTech, Integrations, ML, and DL. Connect with me over LinkedIn or Gmail.
  • 📫 You can reach me over mail - harsha.rv67@gmail.com

        

Pinned Loading

  1. binary-random-sequences binary-random-sequences Public

    Classify Human vs Computer generated random binary sequences. Perform PCA and arrive at conclusions based on results.

    Jupyter Notebook

  2. mnist-classification mnist-classification Public

    In this project you manually train a multilayer perceptron (MLP) deep neural network using only numpy. Do not use tf.keras, pytorch, scikitlearn, etc.

    Jupyter Notebook

  3. mnist-classifier-and-lms mnist-classifier-and-lms Public

    Jupyter Notebook

  4. pattern-recognition pattern-recognition Public

    Code repo to learn, analyze and develop classification models

    Jupyter Notebook 1

  5. algorithms-analysis algorithms-analysis Public

    Analysis of image processing algorithms on AWS Graviton 2 as compared with Tesla T4. The algorithm was executed and results was reported

    C++

  6. polyvore-fashion-compatibility polyvore-fashion-compatibility Public

    Devised a solution to a fashion compatibility problem based on the Polyvore dataset. Created a category and fashion compatibility classifier.

    HTML