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Learn how to design, develop, deploy and iterate on production-grade ML applications.
Learn OpenCV : C++ and Python Examples
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
A collection of pre-trained, state-of-the-art models in the ONNX format
A course in reinforcement learning in the wild
PyTorch implementation of AnimeGANv2
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.
Hands-On Reinforcement Learning with Python, published by Packt
Some fun and useful projects with Python
Facenet implementation by Keras2
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Assignments and notes for the Self Driving Cars course offered by University of Toronto on Coursera
This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scra…
YOLOv7 Object Tracking using PyTorch, OpenCV and DeepSORT
I have published my face related codes in this repository
Coursera Generative Adversarial Networks (GANs) Specialization
One Shot Learning Implementation
Using a U-Net model to segment clothing items in an image
This is the implementation of the unit LSTM cell
Using UNet to segment and clasisify the tumours on an MRI brain scan
Exploring non-gradient-based learning techniques for training neural networks, using brute force parameter search and optimization methods. Includes comparison with gradient-based learning.
A deep learning project by the RAIN-INN community focused on accurately classifying various types of fruits, transfer learning, data augmentation, and image processing.
This Is an updated and more improved version of the Toxic Comment Classification with an LSTM I did earlier
Action Recognition with Raspberry Pi and Pimoroni Pan-Tilt HAT Camera