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Hi Guys wave Myself Srajan Chourasia

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srajan-kiyotaka

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Iโ€™m currently learning ๐Ÿ’ฆ GAN, and how to Combine โœจ Models with ๐Ÿ•น๏ธ Hardware to Perform Various ๐Ÿ’ป Task!

I have a strong interested in ๐Ÿ€ Deep Learning, ๐Ÿ‚ A.I/ML, ๐Ÿ”– RL and their applications in different fields like ๐ŸŒŒ IoT, ๐ŸŽ Web development, and ๐Ÿค– Robotics.

Iโ€™m looking to collaborate on ๐Ÿฌ Deep Learning, ๐ŸŽด AI/ML/RL and ๐ŸŒ€ python libraries or projects.

Ask me about ๐ŸงŠ Deep Learning, ๐Ÿ”ฎ AI/ML, ๐Ÿฃ Reinforcement Learning and there application in various domains.

Fun fact I love Watching Anime ๐ŸŽ and Reading Manga โ›ฉ๏ธ

๐ŸŒ Connect with me:

www.linkedin.com/in/srajan-chourasia-007880207 srajanchourasia srajan_kiyotaka tatsuya yukihira @srajan_chourasia 20237834 @srajanchourasia @srajankiyotaka srajan.ash

๐Ÿ’ป Languages and Tools:

Categorya Tools
Languages c โ€œcplusplusโ€ python javascript haskell
AI/ML/DL/RL tensorflow โ€œpytorchโ€ โ€œkerasโ€
Libraries opencv pandas seaborn scikit_learn matplotlib numpy
Web Development html5 css3 mysql
Software and Tools anaconda matlab vscode vim bash
OS linux
๐Ÿ“ฆ Python Packages:

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๐Ÿ“Š My GitHub Stats!

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๐Ÿ’ฐ You can help me by Sponsoring and supporting my Open-Source Work โค๏ธ

With โค๏ธ from India ๐Ÿ‡ฎ๐Ÿ‡ณ

Srajan Chourasia's Projects

ai-ml-dl-resource icon ai-ml-dl-resource

Artificial Intelligence, Machine learning and Deep Learning Resources. ๐Ÿš€ FREE AI/ML/DL Resources - ๐ŸŽ“ Courses, ๐Ÿ“ Blogs, ๐Ÿ”ฌ Research, and many more - for everyone!

applied-ml icon applied-ml

๐Ÿ“š Papers & tech blogs by companies sharing their work on data science & machine learning in production.

bayes_net_sample icon bayes_net_sample

โšก Python library to compute an input probability query on a given Bayes net on discrete random variables using Prior sampling, Rejection Sampling, Likelihood weighting and Gibbs sampling.

coconifiai-face-recognation-cum-reverse-search icon coconifiai-face-recognation-cum-reverse-search

Face recognition system which learns to recognise faces. Only one image is sufficient for the model to recognise the person. But that's not it if the image of the person does not match any face available in the database then We have also provided an option to do a reverse image search on the unknown face to extract the metadata of similar images.

cocoonifyai icon cocoonifyai

We are trying to make a AI capsule which contains all the basic and very useful Ai algorithm, ML Models, DL Models and many more. All these Models are prebuild on the dataset and the user just have to import the library and can use any model into the code without creating a new model, or training/testing on different architecture or datasets, just use the library and write wonderful programs. All the models will be light weight. User can also see the data analysis of the dataset which is used to train the model as well as the model architecture. There are many more features but this the basic idea behind the library.

codehelp-dsa-busted-series icon codehelp-dsa-busted-series

This repo is creating providing students easy access to all the programs taught under Codehelp's DSA Busted Series.

detr icon detr

End-to-End Object Detection with Transformers

dsa-cracker icon dsa-cracker

This is an attempt to solve 450 questions carefully curated by Love Babbar.

dungeons-and-dragons icon dungeons-and-dragons

Dungeons and Dragons is a fantasy tabletop RPG where players create characters, explore dungeons, fight monsters and interact with a fantasy world. Players take on the role of elves, dwarves, humans, etc. and embark on adventures.

face-mask-detector icon face-mask-detector

I used Deep Learning CNN Model to Detect Whether The Person is Wearing a Mask or Not in Real Time Using Web Cam.

free-ai-resources icon free-ai-resources

๐Ÿš€ FREE AI Resources - ๐ŸŽ“ Courses, ๐Ÿ‘ท Jobs, ๐Ÿ“ Blogs, ๐Ÿ”ฌ AI Research, and many more - for everyone!

hackthegames icon hackthegames

All The Codes Used in The Workshop of HackTheGames Event in the Cepheus'22.

haskell-recipe icon haskell-recipe

This repository contains the recipe to become good in Haskell, It contains various Practice Question as well as there solutions. It also contains basic codes of various Haskell tasks.

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