Common AI Types and Real-World Applications | Deep Learning From Scratch

Narrow AI is the only kind of AI that exists today. Learn the three types of AI, the three ways machines learn, what deep learning adds, and where each one is at work in the real world. Welcome to Keduka AI School’s Deep Learning From Scratch. This lesson sorts artificial intelligence into its three types by capability: Narrow AI, the specialist that exists today; General AI, the well-rounded mind that remains a research goal; and Superintelligence, purely hypothetical. It then shows how today's narrow AI actually learns: machine learning in three styles, supervised, unsupervised and reinforcement, each with its mathematical shape and its practical examples; deep learning, with its many layers and its three main architectures; a tour of real-world applications industry by industry; and a decision guide for choosing a learning style, with the best practices and the tools you will hear about. Continue learning: https://keduka.com/ Watch the full playlist:    • Deep Learning From Scratch   IN THIS LESSON • The three types of AI as a ladder of capability: Narrow AI (exists today), General AI (a research goal), Superintelligence (purely hypothetical) • Narrow AI is the only type of AI that exists today: every product you use is a specialist at one job • Machine learning: patterns learned from data instead of rules written by hand • Supervised learning: labeled data and a function f that maps X to y; spam detection, medical diagnosis, image recognition • Unsupervised learning: no labels, hidden structure; customer segmentation, anomaly detection, recommendation systems • Reinforcement learning: agent, environment, state, action, reward and policy, and the discounted return J(π) with gamma • Deep learning: networks with many layers that learn their own features; CNNs for images, RNNs for sequences, transformers for language • Real-world applications in healthcare, finance, retail and marketing, transportation and beyond • Choosing a learning style, five best practices, and the tools: TensorFlow and Keras, Scikit-learn, MLflow, Matplotlib CHAPTERS 00:00 One job, done brilliantly 01:29 What is artificial intelligence? 01:58 The ladder of capability 02:39 Narrow AI: the specialist 04:20 General AI: the well-rounded mind 05:37 Superintelligence: beyond the best human 06:42 Quick recap: the three types 07:18 How AI learns: machine learning 08:35 Supervised learning: learning with a teacher 10:32 Unsupervised learning: finding structure 12:08 Reinforcement learning: learning by doing 15:16 Comparing the three learning styles 16:03 Deep learning: many layers 18:08 Real-world applications by industry 21:29 Choosing the right learning style 23:00 Conclusion Study reminders: narrow AI is the only type that exists today; machine learning learns patterns from data, not rules written by hand; supervised learning needs labels, unsupervised learning finds structure, reinforcement learning learns by interacting; deep learning is not a fourth learning style, it is machine learning with many layers; every real-world application is a narrow AI system doing one job well. Subscribe to Keduka AI School for visual lessons that build your understanding of artificial intelligence, one idea at a time. #DataScience #KedukaAISchool #AI #MachineLearning #DeepLearning #NeuralNetworks #Transformers #CNNs #RNNs #LLMs #NLP #ComputerVision #OpenSource #MLOps #DeepLearningTutorial #AIEducation #ModelTraining #DataAnalysis