ramapinnimty Goto Github PK

followers: 12.0 following: 66.0 repos: 31.0 gists: 0.0

Name: Rama Krishna Pinnimty

Type: User

Company: Virginia Tech

Bio: I'm an aspiring Graduate Student interested in Software Engineering and Data Science.

Twitter: ramapinnimty

Location: Blacksburg, VA, USA

Blog: www.ramapinnimty.com

Hi there 👋🏻, I'm Rama Krishna Pinnimty!

Here's a bit about me :

🎯 I’m currently working on Generative-based Deep Learning models, specifically StyleGAN.
👨🏻‍💻 I am currently learning about Natural Language Processing and AWS.
💬 Ask me about Machine Learning, Web & Software Development, or Computer Science in general, and let's collaborate to knock new ideas to code.
🧔🏻‍♂️ Pronouns: He / Him / His

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Rama Krishna Pinnimty's Projects

coding-interview-university

A complete computer science study plan to become a software engineer.

contribute-to-open-source

Learn the GitHub workflow by contributing code in a fun simulation project

cs5644-twitter-sentiment-analysis

cs5664-amazon-product-recommendation

This project includes the implementation of a product recommender system based on product reviews and metadata history (product titles) from the Amazon Product co-purchasing Network metadata dataset.

cs5704-se-vault

Official SE-VAULT Project Repository for the team Root_Mean_Square.

cs5814-autocodedoc

Using Deep Learning to Generate Automated Code Documentation Across Multiple Programming Languages.

cs5914-infinity-travel

Infinity Travel – Flight Booking Service

data-science-interview-preperation-resources

Resoruce to help you to prepare for your comming data science interviews

face-fetch

A fast, efficient, and scalable Face-Retrieval System that relies on the slight impressions of the target face which a user has envisioned.

grokking-patterns-leetcode

Mapping the 2022 Grokking Coding Interview Patterns to LeetCode

hands-on-tensorflow

Systematic and complete notes (or guide) on getting started right away with Tensorflow. Inspired from "Complete Guide to Tensorflow for Deep Learning with Python" on Udemy.

A multi-level (2 levels) CNN model was built using Keras to classify Hindi characters from 5 classes. The training and validation accuracies were 99.2% and 98.9% respectively. The model was then used to predict the class labels of new images and it has done its job quite well. All the results and statistics are clearly mentioned in the notebook along with interactive visualizations.