Build & train supervised machine learning models for prediction & binary classification responsibilities, together with linear regression & logistic regression
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• Implement best techniques for machine learning improvement so that the models generalize to knowledge and responsibilities in the real entire world.
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• Build machine learning styles in Python utilizing preferred machine learning libraries NumPy and scikit-find out.
• Create recommender units with a collaborative filtering approach as well as a content-based deep learning technique.
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Amazon SageMaker is a completely managed provider that provides each and every developer and info scientist with the opportunity to Develop, practice, and deploy machine learning (ML) styles immediately.
Implement greatest practices for ML development & use unsupervised learning approaches for unsupervised learning together with clustering & anomaly detection
These lessons are optional and are not necessary to accomplish the Specialization or apply machine learning to true-entire world assignments.
• Make and practice supervised machine learning models for prediction and binary classification tasks, such as linear regression and logistic regression.