Jaganadh Gopinadhan's Projects
Adaptive Synthetic Sampling Approach for Imbalanced Learning
Software Engineering for Data Science
AWS AI ML Architecture Workshop Competition code
Centralizes Azure FinOps information and tools to enabling a better understanding and optimization of cloud costs
Code and model for AzureML sklearn pre-trained model usgage
Back to Basics
Importing all the Open Source Code I written before 2012 in Bitbucket
Experiments on summarization-driven book generation
The repository for the draft text of my driverless cars thesis for Comparative Media Studies at MIT.
My notebook on Data Science
Some re-formatted data for experiments
Deep Learning Associates Consulting Services
3D bin packing is a classical and challenging combinatorial optimization problem in logistics and production systems. An effective bin packing algorithm means the reduction of total packing cost and increase in utilization of resources. Because the cost of packing materials, which is mainly determined by their surface area, occupies the most part of packing cost, and in many real business scenarios there is no bin with fixed size, so AI Department of Cainiao proposed a new type of 3D bin packing problem. The objective of this new type of 3D bin packing problem is to pack all items into a bin with minimized surface area. And a DRL method based on the sequence-to-sequence model is proposed to solve the problem. This is the research paper link: https://arxiv.org/abs/1708.05930. Source code of this method can be found in the project.
Eigenvector Metal Etch Data Parser - Python
Config files for my GitHub profile.
Jaggu's new blog page from github :-)
My code used for Kaggle restaruent revenu prediction
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent