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Kursteilnehmer-Bewertung und -Feedback für Maschinelles Lernen von Stanford University

4.9
121,373 Bewertungen
29,802 Bewertungen

Über den Kurs

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas....

Top-Bewertungen

CC

Jun 20, 2018

good course; just 2 suggestions: improve the skew data part (week 6) and furnish the formula to evaluate the number of iteration in the window from image dimension, window dimension and step (week 11)

NN

Oct 15, 2016

It's a good introduction - not too complicated and covers a wide range of topics. The programming exercises are well put together and significantly help understanding. The free Matlab license is nice.

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25576 - 25600 von 28,935 Bewertungen für Maschinelles Lernen

von Bill S

Sep 06, 2019

Thank you for the great course that leading me to machine leaning!

von muhammad i

Sep 06, 2019

great afford of teacher and also wants to improve this course machine learning are helpful for engineer flied thanks for cousera

von Arpit T

Sep 06, 2019

One word PERFECT

One of the best course of machine learning

von Biki D

Sep 06, 2019

superb instructor

von Pablo I C T

Sep 06, 2019

Great course and totally up to date material and concepts. Thank you very much!

von rahul s

Sep 07, 2019

Great Booster course to understand the basic aspects and what goes behind the algorithms, what parameters to focus on, what strategy to follow in different scenarios!!!

von Guanzhou K

Sep 07, 2019

Not else. Just want to say that is pretty good.

von xiekezhe

Sep 07, 2019

非常好

von guillaume

Sep 29, 2019

通俗易懂的介绍了机器学习的主要算法,吴老师的讲的很有耐心。

von Silviu-George P

Sep 29, 2019

It's a great introduction to machine learning and artificial intelligence, I recommend it as someone who didn't knew anything on the subject. The materials are great and the programming exercise are a good hands on experience.

von ash

Sep 29, 2019

i am excited

von Peter A

Sep 30, 2019

Recommended for developers. This is a great introduction into Machine Learning principles at low-level, well balanced between theoretical and practical knowledge. Professor Andrew Ng is an excellent teacher, his presentation skills are amazing and the way he simplifies and explains complex topics is extremely helpful.

von Stephen C

Sep 30, 2019

This course covers key topics in machine learning. The explanation of the concepts is far better than many other machine learning books and courses. The exercises are instructive and the Octave programming system is easy to learn. Andrew also provides many practical tips on how to apply the theories and these are very valuable for a practitioner.

von Thyagaraj T

Sep 30, 2019

An amazing course that helped me to become a data scientist and puts me on the right path. Easy to understand and able to follow even with minimal knowledge.

von 徐鹏

Sep 30, 2019

非常感谢老师详细的讲解,受益匪浅

von Gu L

Sep 30, 2019

Really helpful courses. Strongly recommend for those who wants to learn Machine Learning

von Victor H M D

Sep 30, 2019

Foi meu primeiro contato com Machine Learning e este curso foi excelente para entender os problemas e os algoritmos que podem ser aplicados. Recomendo para quem esta iniciando.

von Esbjörn E

Sep 30, 2019

Very good, very thorough course. Very little redundancy och good focus. I very much appriciate to be able to study this course online.

von Mustafa A H

Sep 30, 2019

It was very helpful and insightful experience. CONCRETELY the best ML course you can find :)

von Nikolai P

Sep 29, 2019

very deep knowledge and at the same time understandable

von SHEIKH M S

Sep 29, 2019

This is undoubtedly one of the best course to start of with towards your entry point in field machine learning journey. Prof.Andrew NG has framed this complete course very effectively in a way that a person who is a beginner in this field will also be able to grasp concepts in a clear and concise manner.

Thank You

Prof.Andrew NG

von Seneca W

Sep 30, 2019

This was fantastic. I was familiar with a lot of the machine leaning topics, but was still able to glean a lot of new information. It was worth the time.

von Milad F

Oct 01, 2019

This is a valuable course which cover many topics of ML without wasting time for redundancies.

von 程环环

Sep 29, 2019

Thank you! I have got a lot in this course, including machine learning algorithm, debugging techniques. The most important thing is a scientific and step by step method to solve problems, not only the machine learning problems, but also the other problems. Keep learning!

von Ann S S

Sep 30, 2019

Excellent Course. Learning a lot from Andrew Ng. He teaches awesome!!