My Portfolio

My name is Chelsea, I study concepts and technologies in the field of AI and ML with the vision of one day having my own company that specializes in Virtual Reality & Computer Vision. On the process of getting there, a lot of skills has to be learned, either for the purpose of attainment of that definite goal or as a way to offer job recruiters my services.

As easy an answer as possible, I thought that the best way to show what I can do is to actually learn those skills and practice on them in terms of short or long term projects. Short term projects are perhaps those that you want to add up in your portfolio while long term might be the ones that complement your overall plans for the(your) future.

Below are a few of the skills I've managed to gather within a few months. What I want the most? To be sufficiently equipped with enough skills, networks, ideas and money that would push me steps closer to my big goal.


  • HTML
  • CSS
  • Web-Development
  • Machine-Learning Algorithms
  • Tensorflow
  • Javascript
  • Git
  • Google Cloud Platform
  • Python
  • SEO
  • Virtual Reality
  • Writing & Research
  • React



I have applied various skills gathered to the implementation of different projects, specifically in the filed of Deep learning. My interest lies in Computer Vision and Virtual Reality fields. The main reason why I build projects is becasue I love to discover real-world applications of any skill I am learning. that was what drove me to build two different websites back the when I was learning web-development. At this point in time, I consider myself solely a beginner in CV & VR but one that definitely makes sure to learn and move a step further each day. I build projects for two main reasons: To develop a good understanding of concepts as I implement them, and secondly, to scale meaningful projects into production services. Moving on, these projects listed inherently describes what I can and have done as a developer, and of course as I learn and develop more expertise, I hope to build applications that would be invaluable to customers and people in general.

  • A Simple Web App to Classify Images

    One of the earliest projects I worked on excluding the assignment from online courses. In this project I used most concept I had learnt to build a simple web app that can predict the classes of images. I basically built the model with Tensorflow and keras, on google Colab and served using Tensorflow Serving built on Docker. Some Technical Information on this project: In this project, I used the Cifar100 dataset from 2014 developed by to build an Image classifier. This dataset consistes of 50000 images distributed into 100 different classes. I faced some overfitting when implementing this, my accuracy was low at first, this made me learn some new techniques that helped resolve that and consequently bumped up accuracy. The technique applied were generally Regularization and Data Augmentation. For full detailed code, refer to my github repo here and also a blog post where I taught how to achieve high accuracy on this dataset here
The web app was built using HTMl as frontend and Python Flask as back-end. The user here has to upload an image and the model returns the top 5 classes the image belongs to. Link to Project Implementation of Image Classification in a Web App