# 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](https://twitter.com/alphasignalai) - [@karpathy](https://twitter.com/karpathy) - Join these subreddits - [r/deeplearning](https://www.reddit.com/r/deeplearning/) - [r/datascience](https://www.reddit.com/r/datascience/) - [r/learnmachinelearning](https://www.reddit.com/r/learnmachinelearning/) - [r/ProgrammerHumor](https://www.reddit.com/r/ProgrammerHumor/) - Follow these instagram handles - [@machinelearning](https://www.instagram.com/machinelearning/) - Subscribe to these newsletters - [AI Summer](https://theaisummer.com/) - [Microsoft Research Newsletter](https://www.microsoft.com/en-us/research/blog/) ## Further Resources The field of machine learning is vast and has aspects varying from pure mathematics to software development. But one must get a basic idea of each aspect before moving forward. Resources listed below are not to be followed in a strictly linear fashion, choose to begin with what intrigues you. ---- ### Maths for AI Essentials - [Essence of linear algebra by 3Blue1Brown](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab) - [What is Automatic Differentiation?](https://www.youtube.com/watch?v=wG_nF1awSSY) - [Mathematics for Machine Learning](https://mml-book.github.io/book/mml-book.pdf) Advanced (optional): - [Gilbert Strang lectures on Linear Algebra (MIT)](youtube.com/playlist?list=PL49CF3715CB9EF31D) ----- ### Basic Coding Skills - [CS50 2022 - Lecture 6 - Python](https://www.youtube.com/watch?v=5Jppcxc1Qzc) - [python-course](https://python-course.eu/python-tutorial/l) Implementation Practice - [From Python to NumPy](https://www.labri.fr/perso/nrougier/from-python-to-numpy/) ---- ### Machine Learning Essentials - [Stanford CS229: Machine Learning Full Course](https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU) - Kilian Weinberger's [Cornell CS47580 class](https://www.youtube.com/playlist?list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS) and [notes](https://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/) - [An Introduction to Statistical Learning](https://www.statlearning.com/) ---- ### Deep Learning Essentials - [Neural Networks: Zero to Hero](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) - [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning) - [Neural Networks by 3Blue1Brown](https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi) - [Spelled out tutorial by Andrej Kaparthy](https://www.youtube.com/watch?v=VMj-3S1tku0&t=133s) Advanced (optional): - [UMass CS685: Advanced Natural Language Processing](https://www.youtube.com/playlist?list=PLWnsVgP6CzadmQX6qevbar3_vDBioWHJL) - [Deep Learning for Computer Vision](https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r) - [Introduction to PyTorch](https://pytorch.org/tutorials/beginner/introyt.html) (Our framework of choice for building Deep Learning applications) - [Dive into Deep Learning](https://d2l.ai/) (learn theory via implementations)
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Yolov8

5/17/2024
Open Source contributions by C

I contributed in PyTorch Docathon H2 2023. I was second on the leaderboard for my contributions

2/14/2024
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
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