## Open Source contributions by ChanBong I contributed in **PyTorch Docathon H2 2023**. I was second on the [leaderboard](https://github.com/pytorch/tutorials/blob/main/docathon-leaderboard.md#:~:text=pytorch/pytorch%23113348-,ChanBong,-22) for my contributions Here are the PRs, you can also find them in the leaderboard in the row with "ChanBong" in it - [pytorch/pytorch#113337](https://github.com/pytorch/pytorch/pull/113337) - [pytorch/pytorch#113336](https://github.com/pytorch/pytorch/pull/113336) - [pytorch/pytorch#113335](https://github.com/pytorch/pytorch/pull/113335) - [#2644](https://github.com/pytorch/tutorials/pull/2644) - [#2639](https://github.com/pytorch/tutorials/pull/2639)
Last changed by  
 
ChanBong
14

Read more

MATHS CLUB IITR

To promote r

12/4/2023
Untitled

Primary Team ID: 17 Secondary Team ID: 34 Abstract Vehicle routing is an important problem in the logistics industry, particularly for last-mile hubs. These hubs are responsible for delivering goods to customers in a specific area, and they need to optimize their routes in order to minimize costs and maximize efficiency. One key aspect of vehicle routing is capturing the accurate weight of the goods to be delivered. This is important because it affects the amount of fuel required for each trip, as well as the capacity of the vehicle. Additionally, if the weight of the goods is not accurately captured, it can lead to delays and other issues in the delivery process This report summerises our approach to solving the dyanamic varient of the vehicle routing problem with pickups and deliveries considered in the Inter IIT Tech Meet 11.0. In what follows, we will describe our appraoch to tackle this problem with techniques from Operatino Reasech and Machine learning. Our current solver is a mixture of the most succesful experiments we have run so far. We also showcase current web and app framework and design. We highlight our appraoch and setup to accuretly predict voluemteric and dead weight of the items provided. Methodology and Approach Volume Estimation from images

1/18/2023
RL

Why NAS NAS is a technique for finding the best possible architechture for neural nets. It takes off the human bias and finds the best archi suited for out needs. What NAS Search Space Types of layer we can experiment with, number of layers, how will they we connected. Often biased as we are the ones to inclue these choices

11/30/2022
Road Map to Machine Learning

Getting into AI Today there are a plenty of tutorials, blogs, videos, courses, memes, college degrees in the market to get you started with the recent trends and concepts. Among all this clutter, we've got you covered with a few trustworthy set of resources that we're personally a fan of and always fall back to: Join the community Follow these people on Twitter @AlphaSignalAI @karpathy

11/30/2022
Read more from ChanBong
Published on HackMD