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6,812 Bewertungen

Über den Kurs

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....



23. Nov. 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.


21. Sep. 2022

Specacular course to learn the basics of ML. I was able to do it thanks to finnancial aid and I'm very grateful because this was really a great oportunity to learn. Looking forward to the next courses

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251 - 275 von 1,529 Bewertungen für Supervised Machine Learning: Regression and Classification

von Boyang H

15. Juli 2022

Although This should be deemed as an Intro Intro Course to Machine Learning, you can not really find a better way to dive into the field. Andrew Ng is one of the best professors you can have in your whole life.

von Daniel J R B

14. Juli 2022

I liked this course, very didactic and with many practical labs where you can experiment and understand all the math behind the ML models, and also learn all the basic programming to implement them using Python.

von aakash b

23. Juni 2022

In the world of today when most people are pursuing courses for an embellishment of their CV, this course shows that the best minds are those which focus only on learning without worrying about the consequences.

von leslie h

29. Jan. 2023

just a really well paced, non bloated curriculum, for what is an extremely hard subject. I had to do everything twice to really get there, especially with the code, but this of course is not unusual in learning

von Devinder K

11. Juli 2022

Very well designed. I am glad that I joined this course. Video embeded questions and quizzes really helped in clearing the concepts.

Lab practices were an added bonus to pace up our learning.

Thank you Andrew Ng

von Julio L

27. Okt. 2022

Excelente curso. El material es básico, apto para principiantes. Las lecciones son intuitivas y fáciles de seguir. Los laboratorios opcionales permiten revisar detalles de la codificación de los algoritmos.

von Azaz B

9. Okt. 2022

The course was amazing. Andrew Ng is my most favourite instructor at online platform and I really enjoyed the course. This course has boosted my confidence and thrill to enhance my career in machine learning.

von Samuel Q

2. Aug. 2022

Lectures are very well made. Support material (jupyer notebooks) is excellent. Awesome course. Great way to brush up on the basics and its also nice to hear Andrew's enthusiasm and passion for machine learning

von Vardan M

8. Juli 2022

This course is next level gives all the intution about machine learning algorithms including linear and logistic regression and also go throug one of the most popular machine learning library named Scikitlearn

von Avi W

9. Okt. 2022

Clear and approaches from the mathematical point of view, which allowed me to better understand, rather than approaching from the ML point of view, which includes its set of unique and often confusing terms.

von Rafael B

26. Sep. 2022

Quizzes could be harder, but I really enjoyed how the course teaches you the underlying mathematical aspects of each discussed model and showing why it works instead of simply plugging a data into a blackbox

von Luis F O

12. Sep. 2022

Loved this course! I took the original course like an age ago, and now this one as a refresher. The content is great, Andrew NG is an awesome instructor, and the quizzes, assignments and labs are just right.

von Bruno P

29. Juni 2022

Great. For me, this course was a personal milestone, where I was able to understand the mathematical roots of machine learning and at the same time its implementation without necessarily decorating libraries.

von José Á A B

15. Dez. 2022

It is amazing how complex concepts and equations were taught in very simple and pertinent ways, stating at every step which understandings were essential and which weren't, etc. Overall, an excellent course.

von Deleted A

13. Nov. 2022

Detailed explanations were excellent. I was able to follow them and get an true understanding of some very powerful ML techniques. Quizzes were just right. Code examples and assignments were very well done.

von Anton

1. Aug. 2022

Great course for complete beginners. I would recommend something different for people with technical backgrounds though - this one is too simple (although I do understand that it is not a bug, but a feature)

von Ashraf H

26. Juni 2022

It was a great learning experience! Thanks to Dr. Ng and to everyone who contributed to creating this wonderful course. The content was very accessiable and made learning such a complex subject, quite easy.

von Sashka W

22. Okt. 2022

One of the best online courses I have ever taken! Excellent real world examples and clear + logical explanation of concepts in a tangible way. 5 stars - would recommend to everyone interested in the topic.

von Hans-Henrik F

12. Okt. 2022

Andrew Ng is a superb educator, he takes you gently throught the ML basics with strong intuitive reasoning where the math could be hairy for some. This balance is fine and Ng is a master in this fine art!

von Pavlo B

21. Aug. 2022

Simple and practical, the course teaches the basic tools of machine learning, logistic and linear regression. It also touches on feature scaling, under- and overfitting, regularization and gradient descent

von Petro S

1. Aug. 2022

First of all thank you for possibility to study this course.

Material is presented in a clear and understandable way.

The examples presented are clear.

Liked the interactive possibilities of laboratory work.

von Aneesh V

28. Sep. 2022

One of the best online course. Even a person with a complete different domain knowldge can successfully complete this course without much dificulty. The math is not deep but to the point. Labs are great.

von Ahmed F

24. Juli 2022

an amazing hands on experience, you not only learn ML but also python on the go and it is a very amusing course and very short to the point, easy to finish with some little effort and concentration on it.

von Jeff W

2. Juli 2022

I started taking the old version and then I heard this one was coming, so I did the new one instead. Much better! Great to be in Python and even clearer lectures. Prof Ng is easy and fun to listen too.

von Surasin T

21. Aug. 2022

This improved version is a lot easier to follow comparing with 3 years ago.

The course has been designed very well. No software installation is required. The couse is using an online tool to do the labs.