Introduction to Machine Learning Introduction to Machine LearningOverview of key background around Machine Learning and preparing you to be successful in the rest of this course.Exploratory Data AnalysisUse AWS SageMaker Studio to access S3 datasets and perform data analysis, feature engineering with Data Wrangler and Pandas. And finally label new data using SageMaker Ground Truth.Machine Learning ConceptsIn this lesson you'll learn about ML Lifecycles, how to differentiate between supervised vs. unsupervised ML, regression methods, and classification methods. Model Deployment WorkflowIn this lesson you'll load a dataset, clean/create features, train a regression/classification model with scikit learn, evaluate a model and tune a model's hyperparameter.Algorithms and ToolsIn this lesson you'll train, test, and optimize on liner, tree-based, XGBoost, and AutoGluon Tabular models. And you will also create a model using SageMaker JumpstartPredict Bike Sharing Demand with AutoGluonTrain a model using AutoGluon to predict bike sharing demand, and see how highly you can place in the competition!CompanyAbout UsWhy Udacity?BlogIn the NewsJobs at UdacityBecome a MentorPartner with UdacityResourcesCatalogCareer OutcomesHelp and FAQScholarshipsResource CenterFeatured ProgramsBusiness AnalyticsSQLAWS Cloud ArchitectData AnalystIntro to ProgrammingDigital MarketingSelf Driving Car EngineerOnly at UdacityArtificial IntelligenceDeep LearningDigital MarketingFlying Car and Autonomous Flight EngineerIntro to Self-Driving CarsMachine Learning EngineerRobotics Software EngineerAI Master’sMaster of Business AdministrationMaster of Science in AIUdacity SchoolsSchool of Animation and Game DevelopmentSchool of Artificial IntelligenceSchool of Autonomous SystemsSchool of BusinessCareer ResourcesSchool of Cloud ComputingSchool of CybersecuritySchool of Data ScienceSchool of DevOpsSchool of Executive LeadershipSchool of Product ManagementSchool of Programming and Development