Kiran Rawat's Projects
In this guided project, I have analyzed a dataset for sentiment analysis. I worked on the PyTorch BERT model and adjusted the architecture for multi-class classification. Furthermore, I have changed the optimizer and scheduler for ideal training and performance.
Books Search Using Google api
This repository includes all the assignments and project work related to the course.
This project is aimed to predict the COVID-19 cases for the next day based on the previous history of the cases. Here, I collected the data, cleaned it and prepared it for modelling. LSTM model is trained on the data to perform the time-series prediction.
Useful sources to learn about DS concepts.
Flask-based restful API that processes metadata requests and determines if there is a possibility of direct glare in the associated image or not.
Flask web application that aims to predict fake news over social media using NLP and Machine Learning.
Followed the django documentaion(https://docs.djangoproject.com/en/3.0/intro/). Brushing up my skills on django.
Analyzing the effect of sentiments of SEC filings on the stock prices of S&P500 companies and predicting a stable portfolio based using LSTM and NLP.
D3.js and React dashboard to understand extreme poverty around the world/countries and various factors associated with it.
I have developed this notebook to perform a data insight test organized by "Deveron UAS". I have performed a detailed analysis of the data and gathered important insights to improve the farming experience.
This repository contains my solution for a few problems from SQL, Python and AI modules for medium difficulty level.
The project aims to analyze the NYC Taxi dataset and draw actionable insights using PySpark, Spark-SQL and Kibana Dashboard.
My personal repository
My portfolio website. Please view the website at https://kiranrawat.github.io/
āļø A Gentle introduction to Kubernetes with more than just the basics. š Give it a star if you like it.
Minimum Viable Study Plan for Machine Learning Interviews from FAAG, Snapchat, LinkedIn.
A booklet on machine learning systems design with exercises
Travel Recommendation and Intelligence Engine
Jupyter notebook showing transfer learning using BigDL and Analytics Zoo