Building Autonomous Systems: A Guide to Agentic AI Workflows
A complete guide to building autonomous systems with agentic AI workflows—covering core concepts, tools, and real-world applications.
Hidden Markov Models Explained
Hidden Markov Models explained in simple terms. Learn how HMMs work, their components, and use cases in speech, NLP, and time-series analysis.
Introduction to Seq2Seq Translators with PyTorch
Neural Machine Translation is the practice of using Deep Learning to generate an accurate translation of text from one language to another.
Hierarchical Reasoning Model Explained
Hierarchical Reasoning Model (HRM) brings a brain-inspired approach to AI reasoning. HRMs reduce memory usage while improving efficiency.
FlashAttention 4: Faster, Memory-Efficient Attention for LLMs
FlashAttention 4 improves LLM inference with faster attention kernels, reduced memory overhead, and better scalability for large transformer models.
The Practical Guide to Advanced PyTorch
Master advanced PyTorch concepts. Learn efficient training, optimization techniques, custom models, and performance best practices.
Prompt-based Learning Paradigm in NLP
In this blog, we discuss various types of learning paradigms present in NLP, notations often used in the prompt-based learning paradigm, demo applications of prompt-based learning, and discuss some design considerations to make while designing a prompting environment.
CrewAI: A Practical Guide to Role-Based Agent Orchestration
Learn CrewAI from scratch with this practical crash course on role-based agent orchestration. Explore agents, tasks, workflows, and real-world use cases.
How to Train A Question-Answering Machine Learning Model (BERT)
In this article, I will give a brief overview of BERT based QA models and show you how to train Bio-BERT to answer COVID-19 related questions from research papers.
