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Hi I'm David 👋

I am Software Developer. I love to learn and share my knowledge with other people.In my free time i read books, mostly ebooks produced by the folks at Standard Ebooks. I have a lot of stuff i have done ranging from mobile applications built using flutter to web appications and machine learning projects.

Some of the things i have done ❤️

Software Engineering

  • Yatshop:Developed the prototype of an E-commerce website builder with a custom Html theme using Rust.
  • Coupon Cutter:Implemented both the frontend and backend of a mobile coupon system using Flutter and Golang respectively.
  • Country Directory: Developed mobile application using Flutter and GraphQL that allows users to search and get basic information about any country in the world

Data Science & Machine Learning:

  • Car Price Analysis and Prediction: Collected and analysed regional car price data using Python. Machine learning models for predicting car prices were developed and deployed using Flask.
  • Bank Marketing Campaign Analysis and Success Prediction: Developed machine learning models for correctly classifying the success of a bank marketing campaign with indepth data exploration and visualization using Python and Tableau.
  • Machine Learning Basics: Implemented popular machine learning algorithms such as linear regression, softmax regression, K nearest neighbor, decision trees, bagging, random forest, etc from scratch using only plain Python and Numpy.
  • HackerNews Project: Using the official API, I scraped over 1.2 million posts and 70k+ usernames to perform EDA and entity recognition on data.
  • Apple Podcast Project: Scraped and published podcast metadata and user reviews dataset for machine learning projects. 

Deep Learning

  • NeuralStyleTransfer: Developed Tensorflow Implementation of A Neural Algorithm of Artistic Style.
  • U-Net Image Segementation: Developed Tensorflow Implementation of the U-Net image segmentation architecture as described in the original paper.

📫 How to reach me: You can reach me through email or on Linkedlin

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