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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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951 - 975 of 1,030 Reviews for Advanced Learning Algorithms

By Abderrahim B

•

Mar 5, 2023

Some of the topics were not explained clearly and found them quite complicated. Topics:

1. XGBoost

2. Bias and Variance

Also, I did not understand why most of assignments were about writing codes for functions that are already implemented in open source libraries and packages!

By Hoormazd Z

•

Mar 22, 2023

Great course. Really easy to follow and it's a good starting point for learning about ML, assuming you already know linear and logic regression. I wish there were more programming assignments and more lectures on TensorFlow though.

By Arshdeep K

•

Mar 19, 2024

I wish there was more on the practical use and coding part. And the labs could be a bit more explained. Apart from all that, its an amazing course and it has helped me understand many concepts clearly from the ground up.

By zia u r

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Dec 17, 2022

Truly peaking, I used hints very often because I was not familiar with the Phyton. A optional week as a zero week should be introduce to teach basic python for the students that have no previous interaction with python.

By Giovanni

•

Dec 29, 2023

I liked but maybe the level is too basic. Anyway for those who have never seen machine learning, it is a beautiful gentle introduction to all the main concepts explained in a super clear and simple manner.

By Brian R

•

Aug 14, 2022

Course material is good and flows well, but are ANNs and decision trees the only advanced algos? Loved the parts on model bias/variance determination and how to fix the model based on the determination.

By Akanksha G

•

Jul 2, 2024

Every concept was explained brilliantly by Andrew Sir. Though the lab sessions code is much simpler so I feel the code level should be increased. Overall the best course to start your ML journey with :)

By Anirban H

•

Jul 20, 2022

Beginner level course, explained simple concepts on neural network specifically Multi-Layer Perceptron & Decision Tree, nothing advanced topics covered. But the explanation is very very good.

By Rohan K

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May 13, 2024

It's a great course, really phenomenal but it lacks a little on the implementation side. It would be better if it had 1 or 2 medium-level hands-on projects included in its structure.

By Prejith S

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Jan 27, 2023

I felt the lab assignment in the Decision trees section was a little too fast to comprehend. Otherwise, it was an excellent course with just the necessary theory and intuition.

By Caio A

•

May 3, 2024

Good to review some concepts if you have an Intermediate level of knowledge and excelent if you're new to the area. Still very light on mathematics, but the course is excelent

By Ruedi G

•

Aug 28, 2022

Very good didactical approach. The labs are straight-forward but test programming skills more than AI expertise. Editing and error checking in the notebooks is poor.

By Kushagra L

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Jun 3, 2024

Very good learning experience. Bit difficult than the previous course on supervised learning, but concepts can be understood if we listen and understand carefully.

By Farouk B

•

Sep 28, 2024

very good course but it needs lab practice , it looks like we just run the code , aand if we want to write by our self it is hard . but thank you so much

By Avdhoot J

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Apr 9, 2024

It would be much better if you link a relevant applied AI course with this package. The course is more of theory, than practical application.

By Abdul-wahab M

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Aug 12, 2024

Explains the working behind algorithms well . But you need to spend time actually building some projects with this knowledge on your own

By Zach S

•

Feb 15, 2023

Pretty great. I kind of wish the assignments were a little more challenging but I realize that it's a beginner level course too.

By Gaurav G

•

Nov 23, 2023

The last week is less boring, it was hard for me to grab to concepts of the last week, it seems everything magically works!

By Céléstin N

•

Sep 8, 2022

The course is very informative but assignments solutions are provided. There is a lack of challenging learners to do more.

By Younas K

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Feb 4, 2024

This one is a little pacy compared to the first one. Maybe the explanation for the math is not as clear as the first one.

By Alessandro G

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Apr 14, 2024

Really good course, maybe some more project-like assignments would be beneficial to assimilate the concepts more deeply

By Prasanjeet K

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May 17, 2024

If the lab materials and implementations were described It would have been the best course on Machine Learning Basics

By Durlov

•

May 20, 2023

Concepts are well explained, but the last Practice Lab had confusing problems that were not well-explained.

By Syed N

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Dec 25, 2023

Amazing Course!! I feel that the Random Forest and XGBoost section could be a little more elaborated.

By CM-A-Jivhesh C

•

Aug 20, 2023

I wished they added neural networks after all the ML algorithms but agains the teaching was amazing