"Any sufficiently advanced technology is indistinguishable from magic." - Arthur C Clarke



AWS is amazon’s cloud platform. I am a certified aws developer


My favourite language. It can be used to do almost anything, from Web development to Machine Learning and everything in between.


R on the other hand is usually used only for statistical computing and visualization.

Machine Learning

Looks like magic, sounds like magic and smells like magic. Machine Learning is a type of artifical intelligence where you get the application to learn or act without explicit instructions.


Best database to use if you are a rebel. NOSQL database is for your inner anarchist where you do not have to worry about structuring your data!


Almost everyone knows these. Nothing to see here.


  • Alexa Custom Skill

    I created this custom skill to help me validate backups taken by our finity360DR application. The backups are made for multiple clients daily from their salesforce account to Amazon AWS S3. The Alexa skill connects to AWS lambda which then uses STS to connect to client account and get backup details. The latest backup is compared to previous backup to make sure the size and number of rows are as expected.


    Alexa Custom Skill
  • AWS Certified Developer – Associate

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    AWS Certified Developer – Associate
  • Pong AI

    This is a great Machine Learning Demo app. The default model has been trained on 10,000 games which the AI played against itself. It was trained using python and tensorflow neural network. It is published in browser using tensorflow.js

    You can also perform your own training where the model will get trained live on your paddle movement! This is a great way to demonstrate the learning part of machine learning.

    You can Play the game here

    Pong AI
  • Tic Tac Toe AI

    This is a classic implementation of TIC TAC TOE enhanced by adding an AI bot to play against. Spoiler alert: HE DOES NOT LOSE!  

    You can play the game here

    Tic Tac Toe AI
  • YOLO object recognition



    I took this video on our roadtrip from Orlando to Coral Springs and decided to test out YOLO object detection on it. Check out the amazing results. The remarkable thing about this technique is how we are able to detect objects passing by a extreme speed. It was also able to recognize people inside cars! And to be fair the railing does look like a bench 🙂



    YOLO object recognition
  • Face Recognition

    I developed this face recognition system on my Raspberry Pi 3B on the Rasbian Stretch OS. I used pycharm IDE on my laptop to remotely code on the Pi. I used the OpenCV 3 library in Python to detect faces using Cascade Classifier. The recognizer uses the LBPH (Local Binary Patterns Histograms) algorithm to recognize faces.

    Face Recognition
  • ELK Logs from S3

    This is an implementation of the ELK stack (Elasticsearch, Logstash and Kibana). Logstash retrieves logs from S3 buckets and stores in Elasticsearch storage. Elasticsearch indexes these logs and Kibana is used to  serve them up to user on dashboard in form of graphs and charts.

    ELK Logs from S3
  • RFD

    Developed a Results Framework Document on google drive for Divisional Commissioner’s Office(Pune). It is used by government employees of various districts to record results.

  • Music Albums Library (Django-Python)

    This Music Library app was built using Django. It lets you create your own playlists and add songs to it. It also lets you add songs as favourites. You can find the app here. Feel free to register and add your own songs!

    Music Albums Library (Django-Python)
  • BenkYou (MEAN Stack)

    BenkYou is a learning management system developed using the MEAN stack.

    You can demo this app here. The login details for Student and Professor login are:

    Username: ninad
    Password: ninad

    Username: bhaskar
    Password: bhaskar

    I performed project management using SCRUM framework of AGILE. You can see how project management was done here.

    I used Bitbucket for version control. You can view the details here.

    The tools used are:

    • IDE: Visual Studio Code
    • Version Control: Bitbucket
    • Project Management: Taiga tool
    • MongoDB service: mlab (database is served through cloud)

    The project is built using Angular5. The routes are protected using authguard. Passwords are encrypted using sha1 hashing. Material Design component is used for form elements.

    BenkYou (MEAN Stack)
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