Shivam Mehta's Projects
30 Days of React challenge is a step by step guide to learn React in 30 days. It requires HTML, CSS, and JavaScript knowledge. You should be comfortable with JavaScript before you start to React. If you are not comfortable with JavaScript check out 30DaysOfJavaScript. This is a continuation of 30 Days Of JS. This challenge may take more than 100 days, follow your own pace.
Another One of the Android Application in Google Developer Tutorial. In Section 2
This Project Was Made by Akshay Saruabh and Me as per our Training Project
A collection of resources and papers on Diffusion Models
Cool links & research papers related to Machine Learning applied to source code (MLonCode)
A simple implimentation of Bayesian Flow Networks (BFN)
Code examples for my Write Better Python Code series on YouTube.
Blockchain Books
Practicing Django
Contrastive Language-Audio Pretraining
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
This application let me change the color of my views depending on the button clicked, it is a good idea for checking handlers and binding of different elements.
Mini website for testing both general CS knowledge and enforce coding practice and common algorithm/data structure memorization.
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport
A tool for creating skeleton python project, built with popular develop tools and conform to best practice.
🐸 - A general purpose model trainer, as flexible as it gets
Python related videos and metadata powering =>
Writing Deep Learning Neural Network for Different Cases
One of The First Android Apps I developed as part of tutorial by Google
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
PyTorch code and models for the DINOv2 self-supervised learning method.
A template for a typical DS project
End-to-End Speech Processing Toolkit
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"