Machine Learning and Artificial Intelligence

Introduction.- Introduction to AI and ML.- Essential Concepts in Artificial Intelligence and Machine Learning.- Data Understanding, Representation, and Visualization.- Linear Methods.- Perceptron and Neural Networks.- Decision Trees.- Support Vector Machines.- Probabilistic Models.- Dynamic Programming and Reinforcement Learning.- Evolutionary Algorithms.- Time Series Models.- Deep Learning.- Emerging Trends in Machine Learning.- Unsupervised Learning.- Featurization.- Designing and Tuning.- Model Pipelines.- Performance Measurement.- Classification.- Regression.- Ranking.- Recommendations Systems.- Azure Machine Learning.- Open Source Machine Learning Libraries.- Amazon's Machine Learning Toolkit: Sagemaker.- Conclusion.