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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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276 - 300 of 1,030 Reviews for Advanced Learning Algorithms

By Amith V

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Jan 30, 2024

Loved the teaching by instructor never made me feel like i dont know anything thank you sir and the team for this course

By Atharv P

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Oct 29, 2023

This course has helped me to get a deep understanding of neural networks as well as various machine learning algorithms.

By Rani D S S

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Jan 5, 2023

Seriously good but need more math content. Prof Andrew Ng, please include more math derivations and advanced math stuff.

By Katam V K

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Jul 29, 2023

There should be some explanation for the labs in the decision trees topic(week 4) apart from that everything is great.

By israel m p

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Feb 23, 2023

Es un excelente curso para adentrarse a algoritmos avanzados de Machine Learning. Andrew Ng y su equipo son excelentes.

By Baris B

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Jul 13, 2022

Great resource for learning basic concepts of neural networks and decision trees. Thanks a lot for making it available.

By Shreshtha Y

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Jul 8, 2024

Easy to understand and learn from. Only improvement would be to explain xgboost and random forest algorithm a bit more

By Alexander M

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Jul 4, 2024

I enjoyed this even more than the previous course in the series and I look forward to unsupervised learning algorithms

By Md. M R

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Apr 22, 2024

Instructor like Andrew Ng. sir, blessing now a days.!! Wish to learn from him face to face!! Best course design ever!!

By Francisco S A

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Jul 25, 2023

Good compilation of some of the most common advanced learning algorithms. Missing some like SVM but great in any case.

By Kartik A

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Aug 7, 2024

Developed a better understanding of machine learning libraries and algorithms along with the mathematics behind them.

By Fangyuan L

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Nov 16, 2023

nice instructor and very useful learning materials, the course is also designed to be very begininger level friendly!

By Mamy R

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Jul 24, 2023

Very strong learning methodology, from easy understanding to abstract content with enriching practices!

Thanks a lot!

By Shawn B

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Aug 15, 2022

Very useful material. I recommend it to everyone interested in learning about practical machine learning algorithms.

By Simpal K M

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May 24, 2023

It was a great course. I am thankful to Andrew Ng and full team who made these difficult concepts a piece of cake.

By Nicholas S

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Jan 23, 2024

The course is informative and easy to follow, building on the material covered in the supervision learning course.

By Mironov V

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Nov 25, 2023

I would like more examples and practical tasks on convolutional neural networks, but otherwise the course is good.

By Juan S G V

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Oct 12, 2023

Un curso especializado muy completo. El profesor es muy dinámico y tiene una excelente manera de hacerse entender.

By Yu K

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Oct 6, 2023

super useful course for those who wants to gain some bascis knowledges about the neural network and decision trees

By Pedro S L

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Aug 20, 2024

Excellent course for learning the basics of Machine Learning. Very well explained and with comprehensive examples

By Duc G

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Apr 29, 2023

Can't explain how important this course to me :D. Keep updating the good work. Many will need it in the future :D

By Gaurav M

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Dec 31, 2023

really organized course, great teaching style, But in decision tree I struggled getting intuition about entropy.

By Mobin V

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Sep 9, 2023

Simple language, Great labs, Good path.

This course is actually a Great Way to Learn Machine Learning Algorithms.

By Umar R

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Oct 19, 2024

This is very good, introduce me about neural network, the lecturer knows how to teach and provide the subjects.

By Mark R

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Jun 4, 2024

Loved this course! It provided a deep understanding of the subject with practical examples. Worth every minute!