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Отзывы учащихся о курсе Advanced Learning Algorithms от партнера deeplearning.ai

4.9
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Оценки: 323

О курсе

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....

Лучшие рецензии

SD

8 июля 2022 г.

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.

SM

5 авг. 2022 г.

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.

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1–25 из 76 отзывов о курсе Advanced Learning Algorithms

автор: Changlin F

22 июня 2022 г.

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

автор: Mohamed N M

23 июня 2022 г.

E​xcellent 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.

автор: Yuriy G

1 июля 2022 г.

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.

автор: Gariman S

15 июля 2022 г.

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!

автор: Billy V

28 июля 2022 г.

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.

автор: Usama A

18 июля 2022 г.

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.

автор: phang y s

5 июля 2022 г.

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

автор: Ovu S

3 авг. 2022 г.

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

автор: Raktim M

28 июня 2022 г.

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.

автор: Edward H

8 авг. 2022 г.

A great course that explains and walks you through actually coding principal supervised learning algorithms. Would appreciate if the description on calculating back propagation from the original course had been included. Then again, this version of the course I actually got through :). All in all I felt the assignments where at a level that I could quite quickly work through, and find help when I got stuck. Grateful that Andrew Ng and his team made this course series subject so accesible and doable.

автор: Chien-Wei C

16 июля 2022 г.

This is by far the best advanced machine learning algorithm course I've ever taken. Using simple examples to convey several no so intuitive concepts. Some of the concepts that was not 100% clear prior to this course are now crystal clear. But honestly, I would say for those who have zero experience in the field of machine learning and coding might find it hard to take in, especially the part when trying to write and understand the algorithm from scratch in the lab.

автор: rcotta

28 июня 2022 г.

Course 2 of 3 from the Machine Learning Specialization series. Whoever read my previous course comments will find this may sound repeating, but once again I need to praise Ng's way to explain the topic, which made clear some details - particularly on the decision trees videos - that were not so clear to me, even after a couple of MBA classes about the topic. I do recommend this course.

автор: Diego C M

18 июля 2022 г.

E​xcellent content to learn how to model, evaluate and implement your first neural network in TensorFlow. Andrew is an excellent and passionate instructor. The assignments in Jupyter Notebooks are very well-curated and effectively help to understand the nuances of the theorical concepts. Thank you!

автор: Carla P

22 июля 2022 г.

Excelente contenido, conceptualmente accesible para iniciar en el Machine Learning y en Redes Neuronales. Tambén la parte de árboles de decisión fue relativamente nuevo para mí y me gustó mucho como se explicó. Infaltables los chistes de Andrew para distraer entre las ecuaciones.

автор: Pritam D

9 июля 2022 г.

My favorite part was how beautifully the concepts from the first class, and more generally linear learning algorithms, are connected to neural networks. The mentors are so helpful, you feel like you have a private tutor teaching you advanced skills. Amazing!

автор: Florian W

16 июля 2022 г.

I really enjoyed the course. Andrew is a great teacher. The examples were well chosen and it was not too complicated to follow. Good to take a look behind the scenes of what the state-of-the-art libraries are doing.

Also +1 on the the dad jokes at the end ;-)

автор: Diana K

15 июля 2022 г.

It is fascinating course! I want to thank Andrew Ng and whole team for very good explanation. Everything was clear, and especially week 3 is full of useful advices. I really enjoyed during this course. Thanks a lot. I am waiting for course 3

автор: Arjun S

18 июля 2022 г.

All the concepts were simply and clearly explained, and the labs ensured that I understood everything in practice. Went from zero knowledge to being able to build my own machine learning programs win a matter of weeks. Excellent.

автор: Shamiso C

27 июля 2022 г.

The concepts are explained in detail without anything rushed or skipped. It is worth it. Thank you for this course, if it wasn't for you, this opportunity would have never reached someone like me in Africa.

автор: Jianhua M

18 июля 2022 г.

The elementary method such as Linear Regression Model more meaningful than the hard method. Dr. Andrew Ng lectures are a very good combination of profound thought and perfect form. Thanks!

автор: stephane d

9 июля 2022 г.

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.

автор: Sai G M

6 авг. 2022 г.

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.

автор: Bruno R S

30 июля 2022 г.

T​his course is even better and more accessible in this new format. This instance is quite complicated, requires some good python/numpy knowledge but the math is not so overwhelming.

автор: Will H

19 июня 2022 г.

An excellent update to the previous Machine Learning course. Goes into excellent detail about each algorithm and the practical notebooks are useful and easy to follow.

автор: Mohammad B

30 июля 2022 г.

The course is very comprehensive and all the concepts are well explained. One piece that's missing is back propagation. other than that, the course is just amazing.