In this project, I'll be building demos for TensorFlow Lite Micro, to be used in conferences and Machine Learning Courses. My plan is to build these...

The aim of this project is to implement various advanced machine learning algorithms for the upcoming textbook "Probabilistic Machine Learning:...

Metric learning is a collection of machine learning approaches for learning to assess similarities and differences between data points from various...

Today libraries like XGBoost and LightGBM dominate most Kaggle competitions on tabular data and achieve state-of-the-art results on a variety of...

For this project, I plan to explore state space models(SSM) and variational inference(VI) in depth. First, I will translate legacy numpy/PyTorch...

I am proposing to publish 4 Collections of models to TF-Hub containing a total of 23 models. Collections will be published from the following models-...

With more than 1 million new diagnoses reported every year, prostate cancer (PCa) is the second most common cancer among males worldwide that results...

I propose to add new loss functions which make improvements over the existing ones for metric learning. I also propose to improve documentation and...

I propose to address the existing challenges with the current codebase of the book and then contribute new code for several figures for the upcoming...

The project will be making contributions to the PyProbML repo helping to build demonstrations and reference implementations for probabilistic machine...

This project aims to add several functionalities to Keras-CV which will be of use to beginner as well as seasoned practitioners. I will be...

Publish fine-tuned MobileViT in TensorFlow Hub TensorFlow Hub is the main TensorFlow model repository with thousands of pre-trained models with...

This proposal aims to provide Tensorflow with more object detection models and tutorial examples. The plan consists of adding...

I will potentially work towards the following problems during the GSoC: 1) I am excited to implement advanced algorithms in JAX and create/re-produce...

KerasNLP is a library for building NLP building blocks such as model layers, metrics, tokenizers, text processing/augmentation techniques, etc. I...

Previous iterations of GSoC combined with recent community contributions have helped TensorFlow catch up with the SOTA in image classification....

Data Scarcity is a Huge and Evergrowing Problem as new tasks and problems are tackled. Sometimes collecting substantial amount of data is almost...

There is a spurt of pretrained edge machine learning models that can be quickly deployed in microcontrollers, thanks to TensorFlow Lite. Reducing RAM...

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving, and interpretation of Decision Forest...

In this project, I propose to create NLP examples using transformer implementations from the Hugging Face Library; by developing easy-to-use and...

This project aims to develop machine learning projects for microcontrollers. This project is a little bit challenging because it is hard to make...

The aim of this project is to create healthcare examples using Keras. I plan to implement new tutorials for: 1. Diabetic Retinopathy detection using...