@mohammed-fahd-abrah

Mohammed Fahd Abrah

@mohammed-fahd-abrahKuala Lumpur, MalaysiaJoined April 2026

Building knowledge, sharing impact through code and AI.

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Data Scientist- AI Engineer - Machine Learning and Deep Learning Engineer

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Mohammed Fahd Abrah's blogs

freeCodeCamp Englishfreecodecamp.org/news10 posts

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Recently published

MFMohammed Fahd Abrahfreecodecamp.orgJul 21 · 28 min read

"Relaxation and its Role in Vision": The 1977 PhD Thesis That Helped Shape Modern AI Research

When people think of Geoffrey Hinton, they usually think of backpropagation, Boltzmann Machines, Deep Belief Networks, or the deep learning revolution that transformed artificial intelligence. But few

MFMohammed Fahd Abrahfreecodecamp.orgJul 15 · 30 min read

AI Paper Review: Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Today, diffusion models power some of the most impressive AI systems ever built. They generate photorealistic images, create videos, synthesize speech, design proteins, and increasingly influence fiel

MFMohammed Fahd Abrahfreecodecamp.orgJul 8 · 27 min read

AI Paper Review: Self-Consistency Improves Chain of Thought Reasoning in Language Models

When Chain-of-Thought Prompting was introduced, it showed that large language models could solve many difficult reasoning problems simply by thinking step by step before producing an answer. It was a

MFMohammed Fahd Abrahfreecodecamp.orgJun 15 · 28 min read

AI Paper Review: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

For the last few years, Large Language Models have been impressing researchers with their ability to generate text, answer questions, translate languages, and perform tasks they had never been explici

MFMohammed Fahd Abrahfreecodecamp.orgJun 3 · 43 min read

AI Paper Review: Training Language Models to Follow Instructions with Human Feedback (InstructGPT)

GPT-3 was a major breakthrough in natural language processing. With 175 billion parameters, it demonstrated remarkable few-shot learning abilities and showed that scaling large language models could u