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

4.6
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7,307 calificaciones
1,334 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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201 - 225 de 1,311 revisiones para Applied Machine Learning in Python

por Andrew

11 de mar. de 2019

Really well explained theory without too much of a mathematical deep dive that provides a perfect set up to learn about machine learning from a purely math/stats perspective through Andrew Ng's Machine Learning course or self study

por Lina J

25 de ene. de 2021

That was a great and challenging course.

I am glad I took it, I learned a lot from the videos and especially from the labs. The last lab took me 5 days to figure out while I was benefit a lot from succeeding in coding it.

Thank you,

por Michael L

17 de jun. de 2017

Excellent high level advance course with in depth explanations. It is well structured. It learn me to applied Machine learning from very basics to optimum level. It help me to understand details of Machine Learning in Python.

por anurag s

29 de jun. de 2017

Clear, smooth and awesome course. Had fun learning the theoretical stuffs . Assignments and quizzes are really helpful in understanding the concepts. Last assignment helped a lot in applying the things learned in this course

por Shreyas M T

22 de sep. de 2018

Everything builds up very nicely on top of each other. A qualm some might have is that part of the assessments might be very simple. However, this is an applied course and the course material stays true to what it promises.

por atul s

21 de may. de 2020

Making ML concepts accessible to the general public. If you are interested in gaining a basic understanding of the broad field, dive right in. Final assignment of Week 4 will really test all you have learned in the course.

por Daniel N

10 de jul. de 2017

I think this course is a real challenge and gives a great introduction to machine learning. I enjoyed it

thoroughly even if I had my troubles with the Quiz questions.. Great course overall, I would recommend it to anyone.

por Mohamed H

26 de jun. de 2018

C'est le meilleure cours en pratique que j'ai rencontré dans toute ma vie.je vous remercie énormément pour m'offrir cette cours et je remercié mon professeur pour la simplicité et la méthode avec laquelle a fait ce cours.

por Dennis W

7 de jun. de 2020

Absolutely must take for hands-on experience and practical knowledge. Instructor explained the tough course material in easy to grasp way. The assignments are challenging but achievable with time and reinforce learning.

por Ashish C

29 de nov. de 2019

This is the best course for machine learning. Assignments are really good. It make sure you know all the things that are taught to you. Even some times I had to go through the lectures again to complete the assignment.

por MARKANTI B S

14 de ago. de 2020

This is one of best machine learning course among I did . It about how to apply machine learning alogrithms rather than explaination how alogrithms works but a brief idea is given about that machine learning alogrithm

por Pablo S C S

25 de ago. de 2019

This course was a very very good introduction to ML focusing on SciKitLearn and using many real-life examples and datasets. Prof. Kevyn Thompson is very engaging and professional. I don't know how it could be better.

por Abhay S

4 de feb. de 2021

A great high-level overview course on machine learning. Great challenging assignments and highly conceptual. Putting everything together, building intuitions on different topics that one can leverage for lifetime.

por Piotr K

29 de nov. de 2017

Great course to gain basic ML skills and start building first models. Excellent starting point. Combined with Andrew Ng`s course on Machine Learning it`s great foundation for futher development as AI specialist.

por Edwin V

17 de jun. de 2020

Machine Learning Fundamentals are taught in concise and easy to understand manner. Some of the ML algorithms such as Kernelized SVM have been explained brilliantly. Thanks for putting up this wonderful course.

por Limber

3 de dic. de 2017

It is a very practical course if you have learned the Andrew Ng's Machine Learning course. It is much much more practical and I have gained a lot from it. I really wish I could learn it soon. Thanks very much.

por Ayush D

30 de may. de 2020

Learned a lot from this course, very informative. One thing have to say that its not for absolute beginners, this course required prior knowledge of ml and python which will ease completion of course. Thanks!

por Leonid I

1 de oct. de 2018

Maybe this would be difficult to implement in a time-constrained course, but it would be nice to have more insight into inner workings of various algorithms... Because otherwise this course resembles botanics.

por Andres M L

8 de dic. de 2020

I loved the course. The explanations are simple and full of day to day life examples. The final assignment was based on a real world problem, showing how the concepts can be applied not just in a play dataset

por Vibhore G

9 de feb. de 2018

From this course you will learn direct application of Machine Learning using python. You can dive into the world of machine learning. Ipython notebooks used are really helpful. Learned a lot from this course.

por Eunis N

20 de may. de 2020

This course made me learn a lot machine learning techniques by experimenting them myself. It's more than just watching the class videos and running the notebook. You need to be ready to get your hands dirty!

por Yingkai

14 de feb. de 2019

It is definitely the best-organized, best-paced, most-worked-on course in this specialization, and from the MOOCs I have ever taken. Strongly recommend for your knowledge and career advance. Great professor!

por Tsuyoshi N

13 de oct. de 2018

Excellent course. I liked the projects in this course to recap the theories that I learned in the lecture and examine the new knowledge that I learned by myself with reading python library documents online.

por Alexandre M

1 de feb. de 2019

Good class, and it's very nice to have the "applied" machine learning angle (as opposed to focusing on the mathematical / theoretical underpinnings, which are only important at a much later point in time)

por Josh B

4 de feb. de 2018

Excellent introductory course to machine learning using python. It covers the basics for the popular supervised machine learning algorithms. I'm excited to build on the knowledge this course has given me.