I am a final year student pursuing my B.Tech in Mathematics and Computing from Delhi Technological University. I am a Tech enthusiast, an Android junkie, Node.js Developer and an AI enthusiast. I love to participate in hackathons, code and develop personal projects & contribute to Open Source Projects.
In Depth Knowledge of concepts such as view binding, permissions, List View, Recycler View, Alarms, Job Scheduler, Broadcast receivers & Notifications.
Threading and Asynchronous programming, Data Storage and Persistence, Networking and JSON parsing using APIs such as Retrofit, Volley and Okhttp,
Image Library such as Picasso and Gson for JSON Parsing, Fragments both statically and dynamcally
in Java & Kotlin.
Used Firebase and it's functionalities such as Realtime Database, Cloud Functions, Storage, Push Notifications and ML-Kit.
Developed over 20+ projects using Android.
Well versed in HTML & CSS, Inheritence rules, usage of selectors, media-queries, keyframes, bootstrap, creating and using npm packages.
Using ExpressJS for creating servers, handlebars for rendering in case of JS disabled pages and jQuery for making AJAX calls in case of JS enabled pages.
MySQL for data persistence, Sequelize (ORM), Socket.IO for real-time communication, MongoDB and Mongoose(ODM) for using NoSQL database,
Authentication using PassportJS & Heroku.
Run Python scripts on NodeJS backend such using custom Sklearn, Tensorflow or Keras pre-trained model for inferencing.
Developed over 10+ projects using NodeJS.
Used common Python Libraries such as Numpy, Pandas and Matplotlib for data visualization, analysing and structuring.
Used requests and beautiful soup library for web scrapping.
Know the working of various ML algorithms such as Linear & Logistic Regression, Naive Bayes, Decision Tree, K-NN, Random Forest, PCA and SVM.
Implemented all algorithms from scratch and using Sci-kit learn.
Used Tensorflow and Keras for building robust Neural Networks such as ANN,CNN and RNN.
Done Text Analysis using NLTK library in Python.
Worked on 75+ datasets using Python Libraries for analyzing, building models and inferencing.
This API acts as a crop advisory app for farmers, extension workers and gardeners. It can diagnose plant diseases, pest damages and nutrient deficiencies affecting crops and offers corresponding treatment measures.
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It is a service that takes long URLs and squeezes them into fewer characters to make a link that is easier to share, tweet, or email to friends.
Used ExpressJS and MongoDB for building API for URL encoding and decoding. mLab was used for hosting MongoDB Database. Deployed on Heroku.
Integrated with Android using Okhttp networking library which was used for asynchronously sending requests to the API for shortening the URL.
Keras was used in training the neural network, the weights of the graph were saved in .h5 format and used directly for inference by running a python script in NodeJS backend.
p5.js for used for drawing into canvas and then using it for further classification of digit drawn. base64 encoding was done for sending images in jQuery's AJAX post method from frontend.
Used Pandas library in Python for data cleaning and structuring. Converted the dataframe to sql database which was used in the backend of Node.js application.
Used bootstrap as front-end framework, ExpressJS and Sequelize for building API. Sendgrid API was used for sending marketing emails.
Responsible for solving doubts by students related to Machine Learning algorithms and Deep Learning using Tensorflow framework and Keras API in Python. Devoting 2 hours each day for doubt session.
Evaluated projects such as Text Classification using Multinomial Naive Bayes and Sentiment Analysis using NLTK.
Designed, managed and delivered a module on Event Based Programming using MIT AppInventor and Logical Programming using Scratch.
Developed games using the concept of sensing, broadcast, cloning, pen tool and list data structure with Logical Programming students and created apps using the concept of canvas,sprite,sensors and media with App development students.