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Avis et commentaires pour d'étudiants pour Supervised Machine Learning: Regression and Classification par

6,766 évaluations

À propos du cours

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....

Meilleurs avis


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 sept. 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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151 - 175 sur 1,529 Avis pour Supervised Machine Learning: Regression and Classification

par seyedeh z k

23 janv. 2023

When I see an expensive car, I wish that one day I would have the same price as the number of students.

Andrew, you made my wish come true!

I am proud to meet you and I am very happy about it ...

I learn that ML is an approach and is a strong culture ! I wish to be able to work and teach in this field one day.

par 【雷涵】Syed

17 déc. 2022

I have been a self-taught ML and Software Engineer, with 3-4 Yo Experience, However, I knew there where a lot of gaps in my knowledge base. This course has filled them. It was fun doing the labs, even if you have take the 2011 version of the ML specialization, this versions is a must for its labs. Thanks.

par Gurkarn S

24 sept. 2022

Very well organized course with detailed explanation of the concepts. The course teaches implementing algorithims from scratch while providing a good fundamental understanding of how the algorith operates. The practice assignments were great since yiu would write the core of the algorithm yourself.

par Arnab C

7 août 2022

As a begineer in Machine Learning, I would suggest this course should be the first one every one takes. Mr. Andrew provides an indepth yet crisp insight of the underlying logics enabling us realise a ML model. Having a bit of very basic math background will help understand the algorithms far better.

par Ziaoulrahman S

25 juil. 2022

A very helful course for beginners the optional labs are tremedous and organised very professionally for beginners those who would like to learn Machine Learning. Background concepts are really well explained with real world examples. The whole course is a peice of Art!!!! Thank you Prof. Andrew NG.

par Sasi k D

24 juil. 2022

A excellent course for those who are into learnning machine learning. This course is explained in detail with wonderful examples which makes the process of understanding easy . And the optinal labs provided with course which have interactive examples gave a great intuition about the course topics

par Bester M

15 janv. 2023

Very nice course. Anybody new to machine learning should be able to grasp the concepts with ease. It's a well delivered, well thought through and slow paced course designed for an effective learning experience. Big thanks to Andrew Ng and the team that put in the hours to develop this course.

par DEEP V S

30 déc. 2022

i really like the course. Its very informative and has good hands on labs. Just a suggestion, it would suit curious minds like me a bit better if links were provided where i could look at the details of the math behind or read a bit into what was taught beyond the course. Great work thankyou

par Rahul C

19 août 2022

Course content and all optional lab are very helpful for the student who are changing their field from Any industry into field of Data Science.

All content are helpful and easy to understand.

Thank you coursera team and Deep Learning team to provide such kind of learning platfrom for biggner.

par Mohamed J

6 août 2022

This is the best course ever on Machine Learning (I hope it remains so in the future) . It was a honour to learn from the great Andrew Ng Sir. Thank you so much sir and to his team for creating such a great course. This course provides a great chance to #BreakIntoAI. I love this course !

par Marc S

3 déc. 2022

This course was incredible. I particularly loved the "intuition" training on the algorithms, so that one can actually see what is happening and how to best adjust things. I think Professor Ng might be the best online instructor I have ever come across. Thank you so much for this!

par Rudra S C

10 oct. 2022

Great course for beginners to Machine Learning. The vastly updated codebase to Python will be very useful for practiioners. The interactive model fits really gives a hands on exploration to beginner Data Scientists. Would be great if you can make the slides available for reference.

par Ovu S

25 juil. 2022

this course is by far the best i have ever taken , both physically and online, and one of the most important aspect of the course if you ask me, i will say it's the optional lab part of the course, because that's where you actually know how to bring the learning algorithm to life

par Wojciech S

4 nov. 2022

Very well explained material on linear and logistic regression (with some additional aspects like regularization, overfitting and underfitting). Knowledge is built step by step, which allows you to consolidate and organize the material. It is worth learning the optional exercises.

par Mohammad A

13 nov. 2022

If I had to review it in a sentence, "This is the best course to get started with Machine Learning in the internet." I tried to learn machine learning earlier but failed. But this time Alhamdulillah I was finally able to understand the things. It will be suggestion to everyone...

par Anna V

7 août 2022

Very clear, concise lectures and materials that were easy to follow. Enjoyed Professor Ng's enthusiasm and encouragment throughout the series. Most liked being able to watch videos and complete work on my own schedule, and also rewatch videos to understand better and take notes.

par rcotta

26 juin 2022

Great course! Provides a very good understanding on how some of the supervised learning algorithms work and makes you code a bit in Python to bind theory and practice together. Ng's explanations are very clear and I had a relevant increase on my knowledge after completing this.

par Temesgen Z

13 déc. 2022

This course is very well organized. It is online, you don't need to be at college to take it. You can take this incredible course anywhere and anytime. Take this opportunities and let your knowledge shine the world. I don't know how to thank the Coursera Initiative community.

par Vinayak C

17 oct. 2022

This is Very useful for those who want to get started with Machine Learning.The course has a very well designed material with great videos, Quizes, Assignments and Practcice Labs.IU myself found it to be really useful and really helped me to get started with Machine Learning

par Michel C

23 août 2022

Very well explained, give a great understanding of the theory. The optional labs are really useful in gaining understanding and developping intuition needed to optimize parameters, especially useful were the programs in the notebook graphically showing optimization progress.

par Noah M

13 janv. 2023

Andrew Ng did a great job explaining machine learning. Lots of math is involved and he explained it in the most simple manner. If you have any experience with programming, the coding assignments are very easy especially as Python has a simpler syntax compared to C++ or Java.

par Abhay D

6 août 2022

This course is a great start for your Machine Learning journey.

I would say that you must have good knowledge of Python Programming as a prerequisite for this course.

Rest, the instructor is too good. He explains everything so well that you don't even need to learn anything.

par Luciano R

31 déc. 2022

A super friendly and pedagogical approach to learning the core concepts of Machine Learning, the syllabus is perfect for people that have some basic math and programming knowledge, and want to get into ML.

Andrew Ng is a superb teacher, one of the best online courses I did.

par Shreyas N

24 juil. 2022

The course is very technical and hence gives importance to nitty gritty of the algorithms used. If you want to learn how the algorithm works and how and when shall we use feature selection or regularization for linear or logistic regression,then this is the course for you.

par Alireza H

11 juil. 2022

It was a really helpful course ,I've learned many useful concepts about supervised learning . practicing optional lab codes and Andrew NG's explanation was admirable, I'm going to enroll the next course in this specialization.

thank you COURSERA ,and thank you Andrew NG :).