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Andrew Ng’s Machine Learning Collection. Courses and specializations from leading organizations and universities, curated by Andrew Ng. Andrew Ng is founder of DeepLearning.AI, general partner at AI Fund, chairman and cofounder of Coursera, and an adjunct professor at Stanford University.
The Machine Learning Specialization is a foundational online program taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
Discover the best courses to build a career in AI | By Andrew Ng | Whether you’re a beginner or an experienced practitioner our world-class curriculum and unique teaching methodology will guide you through every stage of your AI journey.
New Machine Learning Specialization, an updated foundational program for beginners created by Andrew Ng | Start Your AI Career Today 🌟 New Course! Enroll in Function-calling and Data Extraction With LLMs
Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn. Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression.
Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.
Mar 6, 2023 · Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (gen...
Andrew Y. Ng.        . Assistant Professor Computer Science Department Department of Electrical Engineering (by courtesy) Stanford University Room 156, Gates Building 1A Stanford, CA 94305-9010 Tel: (650)725-2593 FAX: (650)725-1449 email: ang@cs.stanford.edu. Research interests: Machine learning, broad competence artificial ...
In CS229, students will learn about the latest tools of machine learning, and gain both the mathematical understanding needed to develop their own learning algorithms, as well as the know-how needed to effectively apply learning algorithms to practical problems.
