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TK's Projects

apollo-client icon apollo-client

:rocket:  A fully-featured, production ready caching GraphQL client for every UI framework and GraphQL server.

astro icon astro

The web framework for content-driven websites. ⭐️ Star to support our work!

autocomplete icon autocomplete

IDE-style autocomplete for your existing terminal & shell

chip8_emu icon chip8_emu

Developed a Chip-8 Emulator in rust that can be run via the command line. You run the program and pass in a path to a chip8 game file, then a GUI will pop-up and allow you to interact/ play the game.

digit_prediction_gpu icon digit_prediction_gpu

Made a model to predict numerical digits with the MNIST dataset using pytorch and torchvision. The model was trained on a GPU and perfomed very well: 97% accuracy.

genql icon genql

Type-safe Prisma & GraphQL Generator for the Node.js Ecosystem

graphql_prac icon graphql_prac

GraphQL Full-stack application made w/ GraphQL, Apollo-server, Urql, PostgreSQL, TypeORM, Redis, Typescript, NextJS, DataLoader

image_classification_resnet9 icon image_classification_resnet9

Image classification model using cifar10 dataset. Model was trained using ResNet9 structure with pytorch and was trained on the GPU.

java_kafka icon java_kafka

Implementation of a kafka producer + consumer using kafka-clients java library

kv_store icon kv_store

Persistent & Memcached compatible Key-Value Store

lr_ecommerce icon lr_ecommerce

Data exploration and using skit-learn to perform machine learning algorithms to help make decisions based of results gathered from the data,

marker icon marker

A Desktop App for Easily Viewing and Editing Markdown Files

nlp-email-spam-detector icon nlp-email-spam-detector

Used a dataset that already had some emails that were classified as spam or not spam. Then clean up the data and removed punctuation and common stopword. After than, I used some sckit-learn's feature extraction class to apply Count Vectorizer and then Tfidftransform. I then applied sklearn's MultinomialNB classifier on that data. I used that trained model to predict if an email was spam or not on a test data and used sklearn's metrics to see how well my model performed.

ref icon ref

Full-stack web app for user-to-user communication. Handles real-time communication and secure user-to-user payment with PayPal's API and Google Pay's API.

rust_wordcount icon rust_wordcount

A command line application that inputs a .txt file format and returns the occurrence of the maximum number of words in that file. Integrated std::fs,std::env and std::io modules in order to implement this program.

sections icon sections

Full-stack application for embedding templates into your website with 3 lines of code.

sections_graphql_server icon sections_graphql_server

GraphQL server using PostgresQL + Redis. Made w/ Apollo server and type-graphql for sections client.

sentiment-analysis icon sentiment-analysis

The model predicts weather a tweet has a positive meaning(1) or a negative meaning(0).

signed icon signed

Full-stack career growth social platform made with Next.js, Redis, Socket.io, Node.js, React.js, TailwindCSS, Typescript, and MongoDB

signed_backend icon signed_backend

Backend for https://github.com/tk04/signed. Made with Typescript, Nodejs,Redis, ExpressJS, MongoDB, and Socket.io. Hosted on Heroku @ https://signed-be.herokuapp.com/

zod icon zod

TypeScript-first schema validation with static type inference

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