neural-networks

Compare neural networks by their feature similarity

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:

Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.

AI-powered padel analytics

PyTorch implementation of Transformer model used in "Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case"

From scratch implementation of a vision language model in pure PyTorch

A beginner's roadmap to self studying Machine Learning and Artificial Intelligence

A Keras CTC implementation of Baidu's DeepSpeech for model experimentation

Integrating Mamba/SSMs with Transformer for Enhanced Long Context and High-Quality Sequence Modeling

Jacobian-Brainwash : A manual alignment tool for large language models built on Anthropic's Jacobian Lens. Results are exportable.

🎧 Automatic Speech Recognition: DeepSpeech & Seq2Seq (TensorFlow)

This repository contains all the work that I regularly did and studied from Medium blogs, several research papers, and other Repos (related/unrelated to the research papers).

Code for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation"

A curated collection of AI learning materials

An all-new Language Model That Processes Ultra-Long Sequences of 100,000+ Ultra-Fast

Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.

BabyGPT: Build Your Own GPT Large Language Model from Scratch Pre-Training Generative Transformer Models: Building GPT from Scratch with a Step-by-Step Guide to Generative AI in PyTorch and Python

Comprehensive LaTeX-based deep learning guide with custom TikZ illustrations

Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.