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  1. Andrew Ng is Founder of DeepLearning.AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University. As a pioneer in machine learning and online education, Dr. Ng has changed countless lives through his work in AI, authoring or co-authoring over 100 research papers in machine learning, robotics, and related fields.

  2. Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course! Solve any problem in your business, job or personal life with powerful Machine Learning models. Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells & more. Go from zero to hero in Python, Seaborn ...

  3. Course 1: Machine Learning in Production. In this course, you will: – Identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements. – Establish a model baseline, address concept drift, and prototype the process for developing ...

  4. Courses. Current courses: CS229: Machine Learning, Autumn 2009. Machine learning is the science of getting computers to act without being explicitly programmed. Over the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and it it also giving us a continually improving understanding ...

  5. The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester. The topics covered are shown below, although for a more detailed summary see lecture 19.

  6. Add this topic to your repo. To associate your repository with the andrew-ng-ml-course topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

  7. There are 4 modules in this course. AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. In this course, you will learn: - The meaning behind common AI terminology, including neural networks, machine learning, deep ...