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Learner Reviews & Feedback for Advanced Learning Algorithms by DeepLearning.AI

4.9
stars
4,921 ratings

About the Course

In the second course of the Machine Learning Specialization, you will: • Build and train a neural network with TensorFlow to perform multi-class classification • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world • Build and use decision trees and tree ensemble methods, including random forests and boosted trees 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 theoretical 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

DG

Apr 14, 2023

Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.

MN

Jul 29, 2023

Another fantastic course by Andrew Ng! He covers neural networks, decision trees, random forest, and XGBoost models really well. I like that he shares his intuition behind every concept he explains.

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1 - 25 of 800 Reviews for Advanced Learning Algorithms

By Yuriy G

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Jul 1, 2022

Slightly disappointed with the assignments to be honest, most of them are too easy to solve, and moreover can be just copypasted from the hints.

Great theory which lacks some demanding practice tasks.

By Changlin F

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Jun 22, 2022

Seems lacking some mathematical details like how to calculate Backpropagation this time

By Mohamed N M

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Jun 23, 2022

Excellent course, although it would have been good to talk more about backward propagation, after finishing this course this is the only point that is left unclear in my mind.

By Sawyer A

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Jul 20, 2022

Just as in the other courses in the specialization, this provides solid conceptual overview, but: 1) too little conceptual practice (the quizzes are short and inanely easy) 2) too confusing labs (for someone with plenty of JS, particularly web-related, but no prior python/data-science experience, I struggled to understand how the data structures were being manipulated and to intuit what the helper functions were asking me to do, and plenty of numpy/python errors that I had to interrogate for too long, distracting from the core concept. On the latter point, I laud their attempt to scaffold with hints, but this needs revision).

By Randall B

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Jul 28, 2022

I finished this course with 3 weeks left in my monthly subscription, only to find out the 3rd course wouldn't be available until the day my subscription ended. I essentially paid for a specialization that didn't exist at the time of my purchase.

By stephane d

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Jul 9, 2022

Great course! and according to me, the ML roadmap that best matches the one I thought to approach the ML topic based on all my experiences. So I recommend this course of Andrew to everyone.

By Amir K Z

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Jul 29, 2022

I was really hoping more detailes on xgboost and unfortunately the course level was very elementary

By Billy V

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Jul 28, 2022

Enjoyed thoroughly the course. The mathematics concepts we’re well explained through exercises that help us visualize the concept behind each equation. The exercises were well thought out to help the student bridge theory to practical coding. People not familiar with mathematical coding will start to understand the pattern behind and be self-sufficient. Thank you for building this wonderful course.

By Gariman S

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Jul 15, 2022

This was one of the best courses I have ever experienced. There was a subtle beauty in the course's planning and Dr Andrew's teaching. The effort Andrew sir made in his teaching was quite evident, and there was a remarkable balance in the difficulty of the course - no matter whether you are a beginner or experienced with Machine learning, you will enjoy this course!

By phang y s

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Jul 5, 2022

A very beginner friendly course that has great explaination on the topic. The programming assignments are really simple and I hope to see harder assignments in course 3 which would allow us to put everything we learn into practice

By Sai G M

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Aug 6, 2022

The course was fantastic! I really enjoyed every part, every video, every quiz, every optional lab, every assignment of the course. It was a pretty memorable ride to have come this far.

By Raktim M

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Jun 28, 2022

The content is excellent but some more emphasis must be given on the discussion of the codes in the Jupyter Notebooks otherwise it'll become less appealing to the once who don't have a good grasp over Python.

By Radu W

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Aug 11, 2022

Nicely presented, however the assignement and the material was too basic.

I would have liked a more rigurous introduction to the subject, that being said I feel I did get something out of this course.

By Abdullah M

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Aug 25, 2022

One of the best explanations of the backend of most advanced ML algorithms. The instructor is the best of the best. Learning new and Advanced Algorithms surely helps you to understand the newer technology and help your hunt down a good job in your future. Thanks to Coursera, Stanford, Deep Learning.AI and Andrew Ng for this very special course and for all of your hard work in making this course go smooth and easy to understand.

By Usama A

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Jul 18, 2022

Amazing, the explaination of the neural netowrks part is amazing wtih very good examples.

The Bias and Variance and the error analyis parts are very good.

I loved giving an idea about more advanced implementations like transfer learning and ensemble learning.

By Alavoine N

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Aug 21, 2022

Really good introduction to machine learning notions and algorithms such as neural network and decision tree, with many informatives details about how to improve them and examples of implementation.

By Ovu S

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Aug 3, 2022

excellent course, for me it's the best online course you can see anywhere

By Deleted A

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Feb 14, 2024

Interesting content! I feel like I'm learning a lot, and I appreciate Dr. Ng's friendly, straightforward explanations. I wish there were more hands-on programming practice; the practice labs etc. often feel like most of the code is written for me and I'm just filling in a line or two. Most of the learning feels like a "sit and get" format rather than a hands-on experience, which makes me nervous about how much knowledge I'll retain and be able to transfer. I also think it's odd that, after introducing vectorization in the first course, the labs consistently seem to push us to write implementations using loops. That concern aside, I am thoroughly enjoying these courses and find them extremely helpful and approachable.

By Chad G

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Jan 10, 2024

Good exposure to ML concepts but the labs were a little too easy. I think if they ever redesigned the course they should give the student the option of coding the algorithms from scratch.

By basil a

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Feb 7, 2024

I think it gets a little messy at the end but aside from that it is a very great course that I would highly speak of an recommend to anyone considering a similar path

By Eric T

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Aug 14, 2022

There are way too many errors on the video's subtitles - not grammatical mistakes, but words completely out of context or even incorrect formulas.

By Saeed V

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Dec 19, 2023

The 'Advanced Learning Algorithms' course, part of Andrew Ng's Machine Learning specialization, has been an invaluable resource for anyone looking to deepen their knowledge of advanced machine learning techniques. The course content, which delves into Neural Networks, model implementation in Python, AGI, Vectorization, Training, Activation Function, Classification, Back propagation, Bias and Variance, Decision Trees, and tree ensembles, has provided a comprehensive understanding of these complex algorithms. The practical implementation and real-world examples, along with the contributions of Eddy Shyu, Curriculum Architect, Aarti Bagul, Curriculum Engineer, and Geoff Ladwig, Curriculum Engineer, have made the learning experience both informative and engaging. Their expertise and dedication to the course content, combined with Andrew Ng's clear teaching style, have truly made this course a standout in the field of machine learning education. I highly recommend this course to anyone looking to advance their skills in machine learning algorithms."

By Vaibhav M

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Aug 9, 2023

Amazing courses that go into detailed explanations about the math and intuitions behind the algorithms without getting too convoluted or making things unnecessarily complicated just for the sake of it.

Prof. Andrew doesn’t just tell you the name of a function for a library (like scikit

learn or tensorflow) and give you magic numbers for parameters. You actually build the model yourself and learn what the parameters stand for and what is the purpose of those parameters and hyper-parameters.

The specialization is well divided into meaningful courses and each course is well structured so that you know exactly what you are going to learn and what key specific skills you will get after completion of a course. Because of the quizzes and practical labs, after completing a course you actually gain confidence that you can design optimized solutions for that particular set of problems.

By Ashish R

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Mar 27, 2024

Again like the previous course , the way of teaching has been exceptional . It motivates me to go look for data sets on all the types of projects that I am enabled to imagin only by the efforts of Sir Andrew and build projects on them . Also I think that completing the course won't land you a job . You really need to put you work and effort on projects and become really good with the skills that is being taught . Making notes is a must because there are a lots of topics being covered in very short span of time. Binge watching the lectures is not good if you really want to learn AI ML . Those topics might wipe off your brain in no time unless you are some super genius being from another planet . Also don't forget to download the labfiles for refrence . They are great source for revison . Thanks

By Revanth J

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Jun 4, 2023

I really appreciate the effort put in by many people, including Andrew Ng and I gave it a 5/5 for so many things, such as intuitive teaching and making the classes and labs enjoyable and fun. But, unfortunately, I couldn't find one thing just not enough and it was, for students like me, who want to enjoy the subject in depth, the course remained a little bit less mathematical, and hence the question why? remained unanswered. I understand that the course is beginner-friendly. But I am a beginner too, and I want to learn more. Though I could do that from other sources, It is always enjoyable when it comes from you. Again, Thank you very much for your time and effort in making Education online, very much helps people across the world.