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

4.9
stars
6,674 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.

SL

Aug 27, 2022

After copleting the course I found all conceptual knowlegde for visualising and implementing the algorithm in my work. Before this course I was not using the full potential of the advanced algorithm

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926 - 950 of 1,030 Reviews for Advanced Learning Algorithms

By Dinesh M

•

Jul 28, 2024

Good

By Ahmed N

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Nov 16, 2023

Good

By chadia e k

•

Nov 11, 2023

nice

By Dini P U

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Oct 14, 2023

good

By Rizki A

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Oct 12, 2023

good

By Trisno P R

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Oct 8, 2023

Joss

By Haveela D

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Sep 19, 2023

good

By Chonchal k

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Sep 14, 2023

good

By Angger M R

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Apr 5, 2023

good

By Fitrah S

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Mar 23, 2023

cool

By Ande R

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Feb 17, 2023

Good

By Lovish C

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Feb 4, 2023

nice

By Marlon S V L

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Jan 15, 2023

Good

By Arkadiusz J

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Mar 5, 2024

:)

By Jaber

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Sep 3, 2022

<3

By Bhavesh P

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Jul 9, 2023

By Serge B

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Nov 30, 2022

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By Will S

•

Jan 3, 2023

Really good conceptual teaching of ANNs and decision trees, but it's a little lacking in the Python implementation. It teaches you how to program an ANN with any number of layers/neurons, but there is no mention of finding the "optimal" number of each. The last week on decision trees and ensemble models feels rushed as there is only one lab and required assignment, so it completely misses the Python implementation of XGBoost. However, it teaches the essential functions in each library, so one can easily continue his or her learning with Kaggle competitions and Stack Overflow. In the end, it's meant to introduce working professionals to the most common ML models in the world today, and it does that very well, but not much more.

By Britto T

•

Jan 6, 2024

This course is brilliance personified especially the intuition (which is the primary focus). The reason for a 4-star rating is, that it ended quickly, and it does not cover the codes in detail, but rather the logic on 'why we do what we do'. Andrew Ng drips knowledge and passion . I only wish he formulates a course named "AI-Scientist" with a one year completion time, that covers topics right from basics of Python, basic math, advanced math, ML, DL, NLP, MLOPs through and through. I am excited to jump into my next course :) Thank you Andrew Ng :)

By Ewa K

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Oct 22, 2023

I am missing handouts from the course and also access to the labs upon completion of the course. It was great that practice labs were offering a lot of help for the student, but I am afraid that too much material was given and the assignment was only about typing the given equation. It leaves me with the feeling that it would be difficult to apply the knowledge from the course to the real word problem, especially that I do not have any code available after the course is finished...

By kiên l

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Feb 21, 2024

Excellent explanation of the concepts by Andrew Ng. However, like other reviewers, I find the last week a little bit rushed and, as compared to the first course of the specialization, this course feels a little...lacking, not in the sense of the information being taught but how the information is being presented (eg. the effort put into making quizzes and labs is subpar ). note: subpar of best is still good so I'd still recommend this one to anyone.

By Nima J

•

Nov 16, 2022

It was a very good and interesting course. I learned a lot about machine learning algorithms.

Compared to the first course "Supervised Machine Learning: Regression and Classification" there were a few things missing:

1- Practical exercises

2- Quizzes during the videos

Although you can learn the theoretical content very well in this course, in my opinion there is a lack of opportunities to practically apply and practice the knowledge you have learned.

By Adnan H M

•

Jul 19, 2022

Explanation: 5 starts Assignments: 2.5 or 3 stars

Thus, overall 4 stars. Andrew did an excellent job in explaining the concepts. However, the assignments, in my opinion, were

too easy (almost just running the cells or typing what was shown in lecture videos). I believe challenging

assignments are an important aspect of any course which this course lacks (unfortunately).

By Jayneel S

•

Aug 4, 2022

The course material and instructor were very good. I just have one complaint for this course... The quizzes are too easy but sure they capture whether you have paid attention in lectures or not, so that is fine. Also a suggestion - If we could be provided with the lecture ppts it would be really helpful revising.

By Vedant R

•

Jun 8, 2023

One of the best mahine learning courses but some of the parts were boring in the middle like week 3 lectures and assignments where you just had theory classes. Some of the parts were very great like all the Decision Tree classes were too good i will never forget how decision tree works now.

Thank you Sir Andrew