Open-source projects and educational resources adopted by researchers and practitioners worldwide.
Simple and ready-to-use tutorials for TensorFlow. Comprehensive guide covering basics to advanced topics with hands-on notebooks adopted by thousands of learners worldwide.
Machine Learning Course with Python. Covers supervised and unsupervised learning, neural networks, and practical applications with interactive examples.
All You Need to Know About Deep Learning — A kick-starter. Curated roadmap covering foundations, architectures, and cutting-edge research with organized resources.
Simple and ready-to-use tutorials for TensorFlow. Comprehensive guide covering basics to advanced topics with practical examples.
Organized resources for deep learning researchers and developers. Curated papers, tutorials, and frameworks across architectures and applications.
Cross audio-visual recognition using 3D CNN architectures for lip reading. Published in IEEE Access with 150+ citations.
A library for speech processing and feature extraction. Supports MFCC, filter banks, and spectral features. Published in JOSS.
Deep learning and 3D CNNs for text-independent speaker verification using synchronized audio-visual features.
Organized resources for deep learning in NLP. Covers embeddings, sequence models, transformers, and generation techniques.
The Roadmap to Learn Generative Adversarial Networks. Covers architectures from vanilla GANs to StyleGAN, with papers and code.
Deep learning examples and tutorials for Microsoft Cognitive Toolkit (CNTK) with hands-on implementations.
Automated customized email sending with Python. Template-based bulk email generation with personalization support.
Sequence-to-sequence models built from scratch in PyTorch. Covers encoder-decoder, attention mechanisms, and beam search.
A comprehensive guide for scalable AI model development and deployment. Architecture, infrastructure, and MLOps patterns.
Correlation-capturing convolutional GANs for generating synthetic healthcare records. Published at FLAIRS 2020.
Research into alignment techniques for large language models, including RLHF, constitutional AI, and transfer learning methods.
Implementation of differentially private convolutional GANs for medical data. Published in Information Sciences (140+ citations).