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Fine-Tuning: The Secret Sauce of AI Magic! Ever wonder how AI gets so smart? It’s all about fine-tuning! Imagine a pre-trained model as a genius with general knowledge. 🧠✨ Fine-tuning takes that genius and hones its skills for a specific task, li

The “Entry-Level” AI Engineer Job Description of 2025 🚨 HR today: > “We’re looking for someone who knows Python, OOP, NumPy, Pandas, SQL, Advanced Excel, Power BI, ALL ML/DL models, every AWS service, LangChain, Docker, Kubernetes, LLM fine-tuning

X updates its developer agreement to ban third parties from using the X API or X Content for training or fine-tuning foundation or frontier AI models.

My Favorite AI & ML Books That Shaped My Learning Over the years, I’ve read tons of books in AI, ML, and LLMs — but these are the ones that stuck with me the most. Each book on this list taught me something new about building, scaling, and underst

🚀 3-Day AI/ML Masterclass – Build Your First AI Project! 🚀 (Mid-May | Online) ✨ Top performers will get a chance to be hired 🎓 Participation certificate for all attendees 📍 Day 1: Python + Data Insights 📍 Day 2: Train Your First ML Model 📍 Da

🚀 3-Day AI/ML Masterclass – Build Your First AI Project! 🚀 (Mid-May | Online) ✨ Top performers will get a chance to be hired 🎓 Participation certificate for all attendees 📍 Day 1: Python + Data Insights 📍 Day 2: Train Your First ML Model 📍 Da

Working on a cool AI project, that involves vector db and LLM fine-tuning

"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin

Machine Learning vs. Deep Learning: What’s the Real Difference? 🤖⚡ Machine Learning (ML) and Deep Learning (DL) are both AI-driven, but they’re not the same! While ML relies on algorithms to learn from data, DL uses artificial neural networks to pr

Overfitting, underfitting, and fitting — these aren't just technical terms, but critical checkpoints in every machine learning workflow. Understanding these concepts is key to evaluating model behavior, improving generalization, and building solutio