| Summary: | Learn to pass the AWS ML Certification Part 2 00:00 Intro 01:56 Artificial intelligence, machine learning, and deep learning. 02:34 Artificial Intelligence 03:10 Machine Learning 03:58 Deep learning 05:11 ML and technology advancements 06:00 Common ML Use Cases 08:14 Types of machine learning 09:21 Supervized learning 10:17 Computer vision 11:08 Unsupervized learning 12:44 Natural language processing 13:20 Reinforcement learning 14:34 Self-driving vehicles 15:04 When to use machine learning 15:35 ML pipeline: Business 16:23 ML pipeline: Data preparation 17:22 ML pipeline: Iterative model training 18:01 ML pipeline: Feature Engineering 19:25 ML pipeline: Model Training 20:18 ML pipeline: Evaluating and tuning the model 21:00 Overfitting and underfitting 22:48 Python tools and libraries 24:57 ML Frameworks 25:50 Amazon SageMaker 26:42 Machine learning managed services 28:30 Machine learning challenges
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