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Opiniones y comentarios de aprendices correspondientes a Applied Machine Learning in Python por parte de Universidad de Míchigan

4.6
estrellas
6,873 calificaciones
1,243 reseña

Acerca del Curso

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

Principales reseñas

AS
26 de nov. de 2020

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

FL
13 de oct. de 2017

Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!

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226 - 250 de 1,225 revisiones para Applied Machine Learning in Python

por Abdirahman A A

13 de ene. de 2019

In depth course that covers a lot in a short amount of time. If you take some extra time to delve deeper into these topics, you can ensure a great overview of machine learning with python.

por Diego A L B

22 de oct. de 2020

EXTREMELY USEFUL AND GOOD COURSE, CONGRATULATIONS TO ALL THE PEOPLE INVOLVE.

Honestly, I never thought I could learn so much in an online course, excited for the rest of the specialization

por Indrajit P

29 de mar. de 2020

Very well structured and informative course ! All the lectures are concise and give enough context for self-exploration. The assignments provide are a good hands-on experience as well !!

por jay s

15 de jul. de 2017

Excellent lectures, good exercises to reinforce the material, and absolutely loved the explanations of the sophisticated mathematical models that made them more lucid and easy to digest.

por Keary P

24 de mar. de 2019

Great for high level concepts and practical applications of machine learning. After taking this course I feel more confident in my ability to work on real world machine learning tasks.

por Andrew G

27 de ago. de 2017

A lot of techniques packed into a relatively short course. Weeks 2 & 4 are noticably tougher than the other two, so allow plenty of extra time for assignment and quiz in those 2 weeks.

por Tian L

20 de abr. de 2020

it is a great course that covers the most important basics of the "traditional" machine learning and helps me build a solid foundation for more advanced machine learning topics later.

por Alan H

8 de may. de 2019

Great course for the applications of machine learning. While I wouldn't recommend for someone with no ML experience, this was a great course for an R user trying to learn more python!

por Rami A T

6 de jun. de 2017

Very helpful and well-structured course, clear lecturing, and high-level assignments. I hope, however, if it can be offered another course specialized in unsupervised learning in ML.

por RAQUIB S

5 de may. de 2020

Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything less than a week,

por Muhammad A

8 de jun. de 2018

I am just about to begins my Module 2 but I have realized that how much easy to understand and to the point course is. I would love complete it and be the proud scientist. Thanks.

por Jesus P I

18 de abr. de 2018

The most practical course I have completed so far. Also the right amount of theory needed to being able to start resolving your first machine learning problems. 100% recommendable

por Ravi M

8 de feb. de 2020

Course was designed in a well structured manner and the basic concepts were covered for Regression and Classification. Many many thanks to University of Michigan for creating it.

por Gogul I

28 de jun. de 2019

This is the best ever course I have taken in Coursera. Learnt very useful ML concepts that are no where available in the internet. Highly recommend this course to ML enthusiasts.

por Mohamed A H

15 de dic. de 2018

Awesome course!

Stick till the end of it, and you'll never regret it.

You're gonna have a lot of fun especially in the last week, don't skip the optional readings of this week ;)

por Malvik P

30 de oct. de 2019

The course is awesome. Professor Kevyn Collins Thompson, explains the topics with examples in python which makes content easy to understand. It is the best course for beginners.

por vishy d

6 de ago. de 2017

It is very good blend of study and practical assignment. Assignments were very well designed to greatly enhance the understanding about the things learned in the video lectures.

por Juan D O V

14 de jun. de 2020

Really good course, although it is more focused on the practical aspect I really learn much more about different machine learning techniques for improving and applying a model.

por Hanbin Z

20 de ago. de 2019

It is a great course. The lectures is interesting and full of knowledge. Though the assignments are challenging, especially the last one, I really learn a lot from this course.

por Valeriya P

25 de jul. de 2017

multi selection questions in quizzes are a bit hard to handle, i think there should be more hands-on experience included. Loved notebooks when one answer lead to the next one.

por Sandilya M

25 de oct. de 2020

The content is so crisp and articulated well. The assignments and quiz need fair amount of work to complete. My fav part of this course is week 4 and tutor nailed it so well.

por Rob N

14 de oct. de 2017

This course was challenging and extremely interesting. The long and detailed lectures and excellent lecture notes covered the material very thoroughly for an online course.

por Jay S

2 de jul. de 2017

Excellent introduction to Machine Learning! The course focus is on supervised ML. Well taught ! Course is well structured with lots of tips & tricks for model evaluation.

por yepi

30 de jun. de 2017

Great course! I have learnt a lot of machine learning skills from this course. Regression, classifier, metrics, clustering. This course cover both theory and practicing. The

por Aayush N

8 de jul. de 2020

A dedicated course with focus on application of supervised machine learning algorithms which can help the student to apply these algorithms in many real-world applications.