Intermediate AWS Machine Learning

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AWS Machine Learning and AI Complete Course

This specialization by Stanford University, taught by Andrew Ng, is a highly popular and comprehensive introduction to machine learning. It covers fundamental concepts including Support Vector Machines (SV Ms) and kernel methods. The course is designed for beginners and provides a strong theoretical and practical foundation.

This course teaches how to implement machine learning use cases for marketing in Python, including predicting customer churn, measuring and forecasting customer lifetime value, and building customer segments.

A Data Camp project that dives into India's telecom sector to analyze customer churn. You'll use pandas and machine learning to study datasets from top telecom firms.

A career track on Data Camp that provides a comprehensive curriculum for aspiring machine learning scientists. It covers a wide range of topics, including supervised and unsupervised learning, deep learning, and natural language processing, with a focus on practical coding exercises.

This course provides a deep dive into the theory of supervised learning, and then applies this theory to practical problems using Python.

An industry-focused introduction to machine learning that covers key algorithms, data preparation techniques, and model evaluation strategies. It is ideal for those looking to apply ML in a business context.

This course from Microsoft introduces the fundamental principles of machine learning using Python. You will learn about various machine learning algorithms, including regression, and how to implement them.

This course from the University of Toronto provides a hands-on introduction to quantum-enhanced machine learning. It covers the intersection of quantum computing and machine learning, focusing on algorithms that are challenging for classical computers. The course emphasizes implementing protocols using open-source Python frameworks and features guest lectures from prominent researchers in the field.