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Отзывы учащихся о курсе Applied Machine Learning in Python от партнера Мичиганский университет

4.6
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Оценки: 6,182
Рецензии: 1,112

О курсе

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....

Лучшие рецензии

OA

Sep 09, 2017

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

FL

Oct 14, 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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151–175 из 1,092 отзывов о курсе Applied Machine Learning in Python

автор: Olin S

Jan 06, 2019

The programming assignments where though because the automatic grader was very picky. Please change it so it gives the user more input about what part of their code is wrong. Also Have a repository where the user can retrieve previous submissions.

автор: reddi m

Apr 18, 2020

Excellent course !!!!! very useful for people who have just completed python and wanted to apply the language. Much more clear when we do the course after studying the libraries of python , very clear explanation throughout the entire course .

автор: Oj S

Jun 01, 2020

It was a great learning experience. The way the course structure is curated is truly adapting to the current trends in field of ML and AI. Thank you for giving me an opportunity to learn from best teachers on a great online learning platform.

автор: Martin G

Jun 23, 2020

Fantastic course theory and material. Additional vague pointers would have been useful for Assignment 4 to help understand required data manipulation not included in the notebooks.

Many thanks to the team and Professor Kevyn Collins-Thompson

автор: LENDRICK R

Apr 07, 2019

A ton of learning, a challenging & rewarding course, the final assignment incorporated concepts & techniques from the first and second courses and gave me a clearer understanding of choosing and implementing machine learning algorithms. :-)

автор: Brian R v K

Oct 30, 2017

This was a great course, with broad coverage of the topic and practical application in Python with scikit-learn. Challenging quizzes were part of the learning context. Overall a great experience, and the best course in the specialization.

автор: Yusuf E

Jul 31, 2018

Excellent overview of many ML algorithms. Challenging quizzes and assignments. The only downside is that some functions like fit_transform, decision_function, predict_proba could have been explained a little better. Great coverage though.

автор: David A d A S

Jul 31, 2017

Awesome.

I learned a lot of fundamentals machine learning. The lectures are very clear and the assignaments focus on practical examples.

I recomend this course for everyone who want to have a global view of machine learning.

I enjoyed a lot.

автор: Michael D

Jul 19, 2017

I thought this was a fascinating course that tried to do the near impossible and succinctly summarise the key techniques of machine learning. And it did that very well. Very challenging tasks, but also overall inspiring for the next step.

автор: Vishesh G

Sep 08, 2018

This was an amazing course that I absolutely loved working on. It gave a deep insight into machine learning. I gained a lot of knowledge from this course. A must for the students who are just stepping in the field of Machine Learning.

автор: Arturo B E G

May 31, 2020

It's a nice course, that accomplishes what it promised: overviewing ML algorithms from an applied perspective; however, I think that some other model selection methods (especially when comparing regressions) should have been included

автор: Ganesh K

Apr 15, 2018

Tough and exhausting, but thoroughly worth it. I learnt a lot - and I already knew machine learning before taking this course. Be prepared to spend a lot of time preparing for the quizzes. The assignments are easier than the quizzes.

автор: Manikant R

May 09, 2020

The course is well taught, by covering a lot of topics in short time, Yes you have to research a lot to get a full understanding, as the ML itself is not easy, you have to do hard work. I liked the references provided in the course.

автор: Andrew

Mar 11, 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

автор: Michael L

Jun 17, 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.

автор: anurag s

Jun 29, 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

автор: Shreyas M T

Sep 22, 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.

автор: atul s

May 21, 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.

автор: Daniel N

Jul 10, 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.

автор: Mohamed H

Jun 26, 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.

автор: Dennis W

Jun 07, 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.

автор: Ashish C

Nov 29, 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.

автор: Pablo S C S

Aug 25, 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.

автор: Piotr K

Nov 29, 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.

автор: Edwin V

Jun 17, 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.