MA
I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.
In the first course of the Machine Learning Specialization, you will:
• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is 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. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
MA
I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.
AA
Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.
SB
This course is a brief but thorough introduction. It has a good mixture of theory and practice.Andrew Ng explains every thing very good, understandable and in a fun way.I highly recommend this class!
WB
amazing course and super easy to follow. my only problem is that it doesn't delve too deeply into the math and science of things and focuses more on practical applications rather than how things work
AM
It is the Best Course for Supervised Machine Learning!Andrew Ng Sir has been like always has such important & difficult concepts of Supervised ML with such ease and great examples, Just amazing!
AK
I learned a lot in this part and would like to continue further but one point that I would like to raise is that it would be better if you can tell us about the in general function that are used in ML
DB
Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.
RK
This course is helped me a lot . I gained some skills related to the supervised learning .this skills i learned in this course is very helpful to my future projects , thank u coursera and andrew ng
RG
The course was excellent, and I gained valuable knowledge throughout. I am also grateful for the financial aid, which allowed me to complete the program successfully. Thank you for this opportunity.
MR
Teaching is an art and Andrew Ng is a great artist. He explained everything in the course in the details and with examples easy to comprehend. Thanks a lot for helping thousands of students like me.
AM
This course has offered invaluable insights and clarity in understanding machine learning concepts. It was a nice journey towards understanding practical application and complex concepts made easy.
FA
The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.