Retour à Apprentissage automatique

étoiles

161,934 évaluations

•

41,533 avis

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....

AD

21 avr. 2017

Very good coverage of different supervised and unsupervised algorithms, and lots of practical insights around implementation. All the explanations provided helped to understand the concepts very well.

EJ

26 mars 2018

Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.

Filtrer par :

par Tomasz C

•14 avr. 2021

Bardzo polecam ten kurs, jak i wykładowcę. Andrew Ng świetnie przekazuje wiedzę, bardzo czytelnie i spójnie przedstawia cały materiał (w naukowy sposób). Na forum kursu można znaleźć wiele przydatnych informacji, a mentorzy pomagają i bardzo szybko odpisują na wiadomości. Świetne zadania z programowania (głownie w Octave) które opierają się na realnych przykładach i wymagają od nas zrozumienia algorytmów (wzorów). 100/100. Serdecznie dziękuje bo wiem że wymagało to dużo pracy, aby stworzyć tak dobry kurs.

par Harsh S

•9 juin 2020

This course is an amazing and extensive resource for machine learning, that isn't afraid to dive into the math behind ML. I thoroughly enjoyed all the intuitive explanations and examples given by the instructor. By focusing on the core concepts of ML, rather than on a specific programming language or library, this course ensures that it stays relevant even years after it was released. Overall, this course may be a little challenging for some people, but it is certainly worth all the time invested in it.

par Jatin k

•18 juin 2020

A very good course for beginners who want to study machine learning. Mr Andrew Ng is a very good teacher and very experienced in machine learning. The course structure is what it should be for an ML course. Programming exercises are really brainstorming and must be solved. Online threads can be used to seek help from other students and mentors, and are really effective. Reading slides are important for making notes.

This course is a very good and effective platform to learn machine learning skills.

par Subham

•3 mars 2019

The real way to learn Machine Learning is this, no black box;understanding using pure mathematics makes it more interesting, and as I was solving the programming exercises I got to know, how simply vectors and calculus can be used to represent complex mathematical formulas. All the hours completing this course was worth. Once I started using machine learning libraries, all concepts were no longer black box for me, suddenly everything started making sense. Highly Recommended course for beginners.

par Elektrons

•24 avr. 2019

This was the hardest thing I've done in ages. I gave up at some point until a breakthrough in programming - I learning to use operations with matrices. I did all programming assignments in python. Couldn't finish the Neural Network - I was stuck for a month because I couldn't wrap my head around mathematical operation in backpropagation. Overall this was a journey. Every morning and evening learning on the way in the bus to and from work. Also lonely weekends. Finished. Can't thank you enough.

par Manish S

•4 févr. 2020

It is an amazing course for beginners who wish to know about Machine Learning. Taking the course and getting high-level knowledge of how different ML Algorithm works can be very useful and (in some cases, it is must) before using any libraries to create solutions. And for such cases, this course is certainly one of the best.

I sincerely thanks to Andrew Ng for taking out his time to make this course for a student like us. I highly recommend anyone to take this course with no hesitation.

par Emily C

•2 janv. 2020

A great introduction to Machine Learning. Found the pace of the lectures just right with a good balance of theory, worked examples and practical tips. I did Maths with Statistics at university and so found some of the concepts familiar but great to refresh! The coding assignments were well-explained and was able to walk through them step-by-step with the instructions. Really enjoyed the course and excited to start testing it out on some problems of my own!

par Vaibhav J

•5 juin 2019

The explanation of each and every topic is so simple and easy. The course is taught by prof. Andrew Ang and covers the major concepts of machine learning. He also provides a good intuition about the topic so to understand them better. Overall this course is awesome and I would highly recommend to someone who is a beginner in Machine Learning. I am very grateful to Professor, Mentors and the Coursera for this amazing journey of 11 weeks in machine learning.

par Issam B

•7 déc. 2020

I'm 50 years old and never thought that a career change can happen at this stage. This course gives you the basics and knowledge of how your trained data is fitted into a model; then used to predict/estimate the output of your next set of data. More importantly, it gave me the confidence to go deeper into the field of machine learning. I'm enrolling to get certified in "Deep Learning Specialization" on Coursera. Maybe we'll meet in your next AI adventure.

par Anup P

•21 mai 2020

This course i actually the first decent course I have taken in Machine Learning. It's really good if you have absolute no idea about what machine learning is. Don't fear the math, because Andrew (the instructor) really explains everything really good. Although a bit of programming experience is necessary, you can cover it while watching the lectures. I wanted to say the Instructor and the Mentors THANK YOU for sharing these extrordinary material with us.

par Burak C Y

•14 févr. 2021

I guess it's been a good start for me. At the beginning it was a bit challenging but after passing couple of weeks it got easier to understand. I think I have learned a lot and I am planning to do more, thanks to the Prof. Andrew Ng, who is the one of the best and most kind teachers I have ever seen. Everything he explains is pretty clear. And the motivational speeches that he made several times were really encouraging. I strongly recommend this course!

par Ken P

•1 mai 2020

Amazing Course by an amazing professor ! I am a Mechanical Engineer, and don't have any IT / Data experience. But even then how Professor Ng laid down ML foundations and took the course forward was very smooth. I am glad I took this course and I hope that the Professor keeps coming out with more advanced videos on ML. Thank you Andrew Ng for the months of work and dedication you put in for coming out with such a brilliant course for us students !

par Andrea R

•3 juil. 2020

Best online course I've ever taken so far, and it's free! Please keep it always free! ML is not my field but thanks to this wonderful course I now have a very good high-level grasp of the argument as well as some technical knowledge to start tackling real-word problems. Andrew Ng is an exceptional teacher. Assignments are a great way to commit theoretical concepts to memory. You will also learn the basics of Octave/Matlab which is useful per se.

par Miklós L

•15 janv. 2019

Amazing class, great lecturer. A really good introduction and overview of machine learning concepts. It often skips the detailed mathematical background, to make it accessible for a wider audience, but I still found that enough information was given that allowed me to work out these details on my own. A lot of effort was put into creating the programming assignments, they provide a great hands-on experience with machine learning algorithms.

par Sara L

•27 févr. 2021

By far the best course you find online to learn the fundamental and math behind machine learning. Despite my hectic life and work schedule, I am grateful and so glad that I took the time to complete this course including all programming assignments and quizzes. I highly recommend this course for anybody who wants to build a strong foundation on AI science and has a sound understanding of linear algebra and some programming experience.

par Antonio R

•23 juil. 2020

Although this is an introductory Machine Learning course, it covers all the important aspects and all the common algorithms, the programming skill is not so necessary with Matlab, a production-ready software, or its free software clone Octave, even if it is needed GPU acceleration. This course was much easier than I expected, even considering the lack of unnecessary mathematical theory, it was teacher Andrew Ng who made it possible.

par Sparsh K

•23 août 2020

Hello this is Sparsh kaushik and i just completed my ML course offered by Stanford.

To be honest this course offered exactly what i was looking, a proper Introduction into the world of Machine Learning.I really appreciate the efforts of prof Ng for making this course and all the mentors who guided me throughout the course.

Overall this course is a must if you are new to ML and want to dive into this beautiful word of data.

par Varadharaj P

•31 déc. 2020

This is the most interesting course that I had ever taken. I want to thank my tutor Andrew Ng for teaching those wonderful things. This course even changed my career path and also made me superior to my teammates by knowing these cool stuff. I have also designed some applications using the concepts I had learned in this course. Lastly I am grateful to my tutor @Andrew_Ng for make profession life more fruitful.

par Alexander H

•22 avr. 2021

This course teaches the fundamentals of Machine Learning very well. Although the use of Octave can be questioned, the exercies generally served as a good addition to the lecture videos. Aside from minor complaints like not editing mistakes from the videos in some occasions, i am very satisfied with this course! Perhaps Prof. Ng could reshoot the lecture videos to improve the video quality in the future.

par Harshit A

•13 janv. 2019

This course is a really amazing and well taught course.Andrew sir is really a very good teacher and he made the complex topics quite easy to understand with his cool examples.Moreover, the optimization techniques and advises given for debugging or improving the machine learning program were really helpful. I hope I can take full advantage of this course and build up a career in machine learning.

par Yan S

•5 déc. 2020

Fabulous course for starters of machine learning.

Even without a solid foundation of linear algebra, calculus, statistics, one can still have a good sense of machine learning by professor Andrew's patient teaching. And the coding exercises helps me a lot in comprehending some concepts that are unclear when watching the videos.

Sincere gratitude for the teacher Andrew. Real respect.

par Shashank S

•9 sept. 2019

This course was splendidly awesome. I am in my final year from grade C engineering college in New Delhi, India. This course helped me a lot to understand about the basics and gave me deep understanding about the field. Thanks to Andrew NG Sir who made this great website for students like us and such an best class content. Highly Recommended to all!

Thank You!

par Pankaj R

•19 avr. 2020

Great Course to start with Machine Learning. All algorithms and technical expects are covered and explained in detail. Assignments are well framed and gives you a proper intuition on algorithms use and performance on real world data. Also appreciate the advise on debugging and optimizing algorithms on small test examples, before running on large data sets.

par Nick M

•12 juil. 2021

I am currently a PhD student in math. Over the years, I have spent countless hours using many different online resources to learn many different subjects. I can confidently say that this course was, by far, the best online resource I have ever used. Thank you Professor Ng for putting so much work into carefully explaining these complex topics!

par Asmita P

•8 avr. 2019

Hi Andrew,

I liked this machine learning course so much. I enjoyed doing all the assignments. I am working in IT industry. I was thinking of working in a new age technology and then my brother told me about this course as I love maths and programming.

I am looking forward to get deep knowledge in machine learning.

Thank you,

Asmita Patil

- Analyste de données Google
- Gestion de projet Google
- Conception d'expérience utilisateur Google
- Google IT Support
- Science des données IBM
- Analyste de données d'IBM
- Analyse des données IBM avec Excel et R
- Analyste de cybersécurité d'IBM
- Marketing appliqué au réseau social Facebook
- Développeur(euse) Cloud Full Stack IBM
- Sales Development Representative Salesforce
- Opérations de ventes Salesforce
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- Automatisation informatique Google avec Python
- DeepLearning.AI Tensorflow
- Certifications populaires en cybersécurité
- Certifications SQL populaires
- Certifications populaires en informatique
- Voir tous les certificats

- cours gratuits
- Apprendre une langue
- python
- Java
- conception web
- SQL
- Cursos Gratis
- Microsoft Excel
- Gestion de projet
- Cybersécurité
- Ressources humaines
- Cours gratuits en Science de données
- parler anglais
- Rédaction de contenu
- Développement Web Full Stack
- Intelligence artificielle
- Programmation en C
- Compétences en communication
- Blockchain
- Voir tous les cours

- Compétences pour les équipes en charge de la science de données
- Prise de décisions basées sur les données
- Compétences en génie logiciel
- Compétences personnelles pour les équipes d'ingénieurs
- Compétences en gestion
- Compétences en marketing
- Compétences pour les équipes en charge des ventes
- Compétences en gestion de produits
- Compétences en finance
- Projets de développement Android
- Projets TensorFlow et Keras
- Le Python pour tous
- Deep Learning
- Compétences Excel pour l'entreprise
- Bases de la gestion d'entreprise
- Apprentissage automatique
- Principes de base d'AWS
- Fondements de l'ingénierie des données
- Compétences d'analyste de données
- Compétences pour un concepteur UX

- Certificats MasterTrack®
- Certificats Professionnels
- Certificats d'université
- MBA & diplômes commerciaux
- Diplômes en science des données
- Diplômes en informatique
- Diplômes en analyse des données
- Diplômes de santé publique
- Diplômes en sciences sociales
- Diplômes en gestion
- Diplômes des meilleures universités européennes
- Maîtrises
- Licences
- Diplôme avec un Parcours de performance
- Cours de BSc
- Qu'est-ce qu'une licence ?
- Combien de temps dure un Master ?
- Un MBA en ligne vaut-il le coup ?
- 7 façons de payer ses études supérieures
- Voir tous les diplômes