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If you want to learn more check our AWS courses: 👉 https://www.cloudwolf.com/ultimate-aw... 👉 https://www.cloudwolf.com/solution-ar... — Get AWS certified in no time. 🔔 Don’t forget to subscribe for more AWS certification prep content and tutorials! / YouTube @CloudWolfAWSA / LinkedIn @CloudWolfAWS / Instagram @CloudWolfAWS In this lesson on the Fundamentals of AI, ML and DL, we focus on Deep Learning — what it is, how it works, and why it’s such a powerful branch of machine learning. We explain how artificial neural networks are inspired by the human brain, how they process inputs through layers and weights, and why adding multiple hidden layers leads to deep neural networks. You’ll also see a practical example of how neural networks learn from data, using house price prediction as an intuitive case study. 🔹 Key Topics Covered: Fundamentals of AI, ML, and Deep Learning Why Deep Learning is inspired by the human brain Biological neurons vs artificial neurons Input layers, hidden layers, and output layers Weights, parameters, and learning through adjustment Shallow vs deep neural networks Why multiple hidden layers = Deep Learning Practical example: predicting house prices What you need to know about Deep Learning for the exam 📘 Perfect for: AWS exam takers, AI & ML beginners, cloud architects, and anyone learning the core foundations of AI, Machine Learning, and Deep Learning. All of our courses available at: https://www.cloudwolf.com/ ⏱️ Timestamps 00:00 – Intro: Deep Learning in the AI/ML/DL landscape 00:30 – Why neural networks matter (Nobel Prize context) 01:05 – What Deep Learning is 01:40 – Biological neurons vs artificial neurons 02:20 – How a neural network processes inputs 03:05 – Weights, parameters, and learning 03:50 – Training with examples (house price prediction) 04:45 – Shallow vs deep neural networks 05:15 – Exam summary & key takeaways 🧠 Hashtags #ArtificialIntelligence #MachineLearning #DeepLearning #AWSExamPrep #CloudWolf #NeuralNetworks #AIConcepts