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Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
18,061 ratings

About the Course

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....

Top reviews

FA

May 24, 2023

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.

JM

Sep 21, 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 of 3,770 Reviews for Supervised Machine Learning: Regression and Classification

By Pradeep C

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Sep 30, 2022

ML concepts very well explained. For practicing and actual world challenge additional resources on Numpy, Tensor Flow, Keras are required. Professor makes this a cake walk to understand core of machine learning concept for new to the field. I am weak in programming still I could see (experience ) the vast expanse of this alien world of machine learning.

By Joshua A Y

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Nov 5, 2023

Excellent course. Great introduction to supervised learning. It helped me cement much of what I already knew on the subject and also gave me a deeper understanding of the course subject. Thank you very much Andrew and the DeepLearning AI team as well as Stanford University and Coursera for this course. I recommend it to any beginner to machine learning!

By Rachana V

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Aug 30, 2023

Excellent course and taught at a good pace which was very helpful for a working professional like me, as I had to squeeze in classes whenever I could. Loved the instructor, Andrew Ng, as well. The explanations were simple, precise and complete and that made a difficult topic seem easier. I'm inspired me to take on a few more courses in Machine Learning!

By Muhammad S S D

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Nov 15, 2022

This is the best course on the internet for supervised machine learning and its basic algorithm. I learned a lot of new concepts from this course and I hope to learn new things after this. Andrew Ng is an awesome instructor . I loved the way the whole course was conducted. All of the topics were simplified and optional labs were very helpful as well.

By ehsan t

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Apr 5, 2023

This course is like a milestone in my career. The very well-structured material was brilliant among other educational courses I ever had. As a person who had no idea about ML, it was a perfect beginning. Also, the encouraging tone of Dr. Andrew Ng alongside his clear educational path in this course is motivating to keep it alive all the way to the end.

By Heath L

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Mar 1, 2023

Thank you so much Andrew and team for these excellently curated machine learning courses. I'm going 2 out of 3 now and I am not losing any momentum because of how you explicitly you explain everything from the main topic down to every details. Again, thank you and I'm hoping I can apply the learnings from this specialization on my work and research.

By JSeco

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Mar 3, 2024

An amazing and comprehensive learning experience and a great way to start with machine learning from ground zero. Being someone with a limited experience in the Python language makes it a bit challenging but still accessible. I really appreciated Andrew's calm teaching style and his great attention to detail. Thank you. Looking forward for course #2.

By SHUBH R

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Nov 25, 2023

It is a very good course for the beginner to start learning ML. It includes learning of regression algorithms like linear regression, logistic regression, and regularization techniques. It helped me a lot to understand these topics. I would like to thank Stanford and the team for making available this type of courses with the option of financial aid.

By Arpan B

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Apr 2, 2023

for someone who knew about ML as much as you would know about the universe from the pop science books, I think this course really dove into the subject with real math and implementations. I can now write python code that can get the program to learn solutions on its own! it almost feels like magic. :)

Thank you Andrew for being such a great instructor

By Giselle L

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Aug 3, 2023

This is an excellent course in ML. Andrew Ng is a brilliant instructor who motives the theory with fun real world examples. It is however a bit of a leap of faith to classify this as a beginner level course. The prerequisites to be able to follow along confidently are a crash course in Python together with undergraduate level algebra and calculus.

By Simpal K M

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Apr 22, 2023

Its a very good course. I knew nothing of ML but after doing this course I am pretty confident that I can implement any supervised machine learning algorithm from scratch. Its beginner friendly. If you are afraid of mathematics and machine learning, you should take this course, because all your fear would be gone by the time you finish this course.

By Aavash B

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Sep 18, 2023

This course is designed to help you grasp the basics of all machine learning models and the math that goes with them. By the end, you'll have the knowledge to work with common regression and classification models. In short, it's a highly recommended course for anyone looking to understand machine learning fundamentals and apply them practically.

By Manuel M G

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Sep 25, 2022

Explicaciones claras y buen material de laboratorios para acercarse al contenido mediante experimientos y visualizaciones. El único punto del curso que podría mejorar son las tareas de programación: considero que tener una mayor cantidad de ejercicios a realizar, quizás más breves pero más frecuentes, haría más fácil asimilar el contenido dado.

By SHIVANSHU U

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Jul 31, 2022

Such a beautiful course I have ever seen about machine learning. No, one can explain like andrew Ng sir . He explain all the algorithm with mathematical aspect too. I can solve all the algorithm with or without sklearn library. Thanks for making these type of course.It is help to make a perfect root of student in the feild of machine learning.

By Rian F J

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Jul 26, 2022

The course is very good since the topic really explains the theory behind the concepts needed for machine learning. Andrew Ng also discusses the concepts very well and the lab assignments are very helpful to solidify the ideas you have to learn from the tutorial videos. I would definitely recommend this course, especially for beginners in ML.

By Valerie D

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Nov 3, 2022

Even auditing it, you learn a wealth of material from the videos. In fact, in some respects, not having access to the optional labs (you have to "upgrade", or subscribe, to gain access) motivates you to create your linear regression code from scratch. That makes it a bit more of a challenge and helps you work on your coding skills as well.

By Jaya K K

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Sep 5, 2022

Professor Andrew NG and his team did a great job yet again with structuring this course. Coming in with some background in Machine Learning, this course for me served as a great refresher for the introductory concepts in Machine Learning. I'm also delighted to take baby steps into python programming and scikit library through this course.

By Geethika I S

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May 24, 2023

Learned a ton. It's a bit to take in. Unless you have a math background I recommend taking the Mathematics for Machine learning course from Deep learning.ai. Anyway I can recommend this course to anyone who's trying to break in to AI. The instructor is the best. And the content is very well structured. Thank you so much DeepLearning.ai Team

By Abraham Y

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May 9, 2023

Andrew does a great job of simplifying complex topics into digestible bites for the student. I have taken other ML courses on another platform, and there, the instructions were merely how to use canned algorithms. I did not learn much there. This course explains some of the math behind the scenes and thoroughly explains the how and the why.

By hassan m

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Apr 21, 2023

After completing supervised machine learning, I get acquainted with fundamental of machine learning and learned about regression and classification algorithms and many other features and how to apply them on over projects. Of course, I want to keep on learning and reviewing materials and learn other courses to be a machine learning engineer

By Amir Z

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Jan 18, 2023

Andrew explained difficult mathematical equations in a manner that make it easier to understand the concept of those strange formulas and actually how they were developed. I believe Although we may not use those formulas in real-world problems but understanding the concept will help us a lot in understanding any machine-learning algorithms.

By José I H

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Jan 11, 2023

Muy buen curso! Logré aprender las herramientas básicas de conocimiento sobre regresión lineal y logística para luego continuar profundizando de forma independiente la librería scikit learn y otras que automatizan los procesos, pero es fundamental saber qué es lo que está pasando al interior! Muy buen entendimiento de los conceptos básicos.

By Sanjay N

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Apr 30, 2023

Prof Ng does a fantastic job explaining complicated concepts in a simple way. The coding requirements are not too egregious and help to solidify the concepts for longer-term retention. I felt that I learned the basics very well, and could furthermore explain them to someone else as well, which is helpful in my work in Product Management.

By Omid S B A

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Aug 16, 2023

this course was really helpful in order to make a person acquianted with the concept of machine learning and it's uses. But it can be better, maybe its my mistake but in optional labs if a person delete cells unintended, there is no way for recovery. So by solving this bug i believe this course and similar courses would be more efficient

By Alexandru-Samuel D

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May 29, 2023

Awesome course. Lots of high-quality material to explain the concepts. Optional code labs to gain intuition and both quizzes and practical labs to strengthen what you've learned. Also, the updated curriculum puts high emphasis on real-world tools (Numpy, scikit-learn) and concepts like regularization, feature engineering, feature scaling.