Chevron Left
Back to Applied Machine Learning in Python

Learner Reviews & Feedback for Applied Machine Learning in Python by University of Michigan

4.6
stars
8,515 ratings

About the Course

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....

Top reviews

AS

Nov 26, 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

Oct 13, 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!!

Filter by:

351 - 375 of 1,550 Reviews for Applied Machine Learning in Python

By Aneek A

•

Sep 30, 2017

Very informative and covers Machine Learning (along with scikit learn) in great breadth!! Would love to see a bit more challenging assignments though.

By Alexandre G

•

Oct 24, 2019

This is a very good course. Probably, much time should be given, especially for Week 2 and Assignment of Week 4. Thank you very much for the course!

By Surya P M

•

Apr 1, 2019

complex topics are explained in a simple way. coding assignments, quiz helped a lot to learn and apply numerous machine learning concepts perfectly.

By Jay N

•

Oct 18, 2018

very very excellent, got to learn whole lot of machine learning models and approaches. i'm straight away going for kaggle competitions after this.

By Carlos F P

•

Sep 20, 2018

It gives a great overview of different machine learning methods. I found useful information that can be missing in other ML courses. Great course!

By Jaydeep D

•

Jul 9, 2017

I am a beginner in Machine Learning. I find this course very easy to follow, interesting and informative. Thank you for the efforts you've put in!

By Jack R B

•

Sep 23, 2020

Great course. A LOT of information but great job at teaching conepts and how to apply them. It got me really interested in Deep Learning and MLP.

By Lucas G

•

Jun 5, 2017

Great course! Really appreciated it, it taught me (and gave me lots of practice) how to use lots of different classifiers for machine learning.

By Manik S

•

Feb 8, 2019

Optional references to the inner workings should be provided. For example how Decision Trees are trained and how the best division is decided.

By Bruno S F C H S

•

Jul 5, 2020

Excellent course to do an overview of many ML algorithms, and with good assignments that help me to fix all the subjects that I have learned!

By Ari S P

•

May 11, 2020

From several MOOCs that focus on ML. I love this course to understand the fundamental off ML and I can easily apply this course in my project

By Zijie L

•

Aug 30, 2018

Easy for beginner to follow. After finishing the course,I'm able to apply simple machine learning algorithms to area I'm currently working on

By James A

•

May 16, 2021

This was the best course in the specialization, in my opinion. I think I learned the most and got the most value from the materials in here.

By Aino J

•

Jun 21, 2020

Practical, applied, and a good overview of how to apply different (mainly supervised) machine learning algorithms using python scikit-learn.

By Santhana C

•

Aug 5, 2017

Nice Course! Lots of useful information packed in 4 weeks. Be prepared spend some extra time if you want to really benefit from this course.

By Eddie G

•

Jan 18, 2021

This course has the perfect combination of theory and practice. It's Intense for a beginner In machine learning but Is absolutely worth It.

By Rajendra S

•

Jan 11, 2019

This course is the one that I enjoyed most while learning anything in Coursera. Thank you everyone associated with this course and content.

By Juan R C C

•

Oct 25, 2017

Good course, content and teaching. Very good weekly assignments allow students to well consolidate course contents on real world practices.

By Nattapon S

•

Aug 3, 2017

It is a good class. I learn a lot from this course. It is a concise starting course for Python machine learning. I recommended this course.

By Jose A P A

•

Jul 14, 2020

Un excelente curso para reforzar lo aprendido en el curso Minería de Datos para la Toma de Decisiones que se dicta en la Universidad Esan.

By Ramon S

•

Dec 7, 2020

Excellent! I had previously done a course on machine learning and it left me with big holes in my knowledge, this really clear things up!

By Moustafa S

•

Jul 28, 2020

GREAT COURSE!, this is one of the greatest courses for applying machine learning and data science algorithms and skills, great great job.

By Ritesh P N

•

Jul 19, 2020

It was amazing course for applied machine learning. The tutor was good teaching core concepts of machine learning algorithms step by step

By Wallace T

•

Sep 8, 2018

Great Course with high practicality. Need more lectures on how to process categorical data. Read the Forum if you encounter any question!

By Fengping W

•

Mar 28, 2018

It is really a good one, and I learn a lot here, both for theory and applied skills. And the reading materials are really good resources