Raghav Sethi's repositories
Face-Recognition
End to End Face-Recognition follows the approach described in FaceNet with modifications inspired by the OpenFace project. Semi-hard triplet loss and online semi-hard triplet generator are used for further fine-tuning.
Autoencoders
The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for the purpose of dimensionality reduction.
go-101
Learn Go
go-file
Upload files faster & safer. GoFile is a blazing-fast & secure file upload service built in Go. Lightning Uploads: Ditch the wait times. ⚡️ Unbreakable Security: OAuth2 & configurable storage keep your files safe. Future-Proof: Scalable architecture handles growing needs.
Open-contributions
This Repository is for Learning purpose, and open contributions under DevIncept program.
pandas_exercises
Practice your pandas skills!
Research-Paper
Deep Learning Fundamental Paper
system-design-101
Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.