Name: Prakhar Rathi
Type: User
Company: American Express
Bio: Data Scientist and Machine Learning Researcher. Keen interest in Financial Machine Learning and Natural Language Processing
Twitter: prakharrathi14
Location: New Delhi, India
Blog: https://prakharrathi25.netlify.app/
Prakhar Rathi's Projects
My academic portfolio website.
A repository to normalize addresses using fuzzy logic
Everything that I have been doing in the AI for trading nanodegree program by Udacity
The official repository for Babel, the Python Internationalization Library
A TV-Show/Movie catalog Web App using ReactJS
Unemployment Rate forecasting tool built for BMWi during the Data Science for Social Good Fellowship
Binary Search Tree in Java
Assignments for CSD 316 Introduction to Machine Learning
Content for the data science winter bootcamp
Automated tool for data story telling
First attempt at creating a flask app
Solve two questions using hypothesis testing and given data
Python Data. Leaflet.js Maps.
Basic analysis of soccer data obtained from Kaggle using Python.
Pod 3.1.3, Team 3
Flappy bird JS
⭐️ Companies that don't have a broken hiring process
YOLO is an extremely fast real time multi object detection algorithm. YOLO stands for “You Only Look Once”. The algorithm applies a neural network to an entire image. The network divides the image into an S x S grid and comes up with bounding boxes, which are boxes drawn around images and predicted probabilities for each of these regions. The method used to come up with these probabilities is logistic regression. The bounding boxes are weighted by the associated probabilities. For class prediction, independent logistic classifiers are used.
Project for the Summer Institute for Computational Social Science 2022
Intellimart: A Smart shopping system during the pandemic
:octocat: (Weekly Update) Python / Modern C++ Solutions of All 1691 LeetCode Problems
Building popular machine learning algorithms from scratch
CMS framework for Django
Our work for the Mindfire Quest with Swiss Re
Machine Learning for Production Specialization
Using MNIST dataset to identify digit images.
A boilerplate code of a recurrent neural network which is also modularized and documented. The only thing that needs to be changed is the form of feature extraction and the number of timesteps.
Building an Image Recognition and Motion Detector System using OpenCV in Python from scratch
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