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Applied Machine Learning in Python, University of Michigan

4.7
3,224 ratings
588 reviews

About this 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

By 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!!

By SS

Aug 19, 2017

the content of videos , quiz and exercise all work extremely well together towards the stated goal of the course i.e. to give the learner a good over view of how to apply ML theories into action

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569 Reviews

By Nitin kumar

Apr 22, 2019

Great Course. Helped me to learn the concepts of Machine Learning and uses of respective Sklearn libraries.

By Qiuxiang Hu

Apr 20, 2019

good course

By Ipsita Dash

Apr 20, 2019

No visible support from groups forum. Videos knowledge is limited to complete assignment or quiz.

By Nattawat Banyatcharoen

Apr 19, 2019

Great!

By Amit Sett

Apr 14, 2019

It would be better if this course was not with Jupyter notebooks. Professional data science projects will not use notebooks but script files instead. The course should prepare students for professional projects by using script files.

Also the lecturing is very rigid and scripted which makes it less engaging. There is also no material on how any of the algorithms work in detail however there is good material on scikit-learn.

By Luis Gerardo Ayala Bertel

Apr 12, 2019

Muy agradecido, mis felicitaciones al Profesor Collins-Thompson, se muestra como una persona amable, dinámica y con alto grado de conocimiento, gracias a sus enseñanzas estoy aprendiendo más sobre el proceso de machine learning, siento que aun me falta mucho por recorrer, sin embargo, a lo largo de este curso aprendí los métodos, tipos de modelos, herramientas tanto para clasificación como regresión enfocándome en el área. De igual forma la literatura es muy interesante, se encuentran artículos que al leerlos vas comprendiendo como ha sido el proceso de transformación en este campo y gracias a esto, se me han ocurrido ideas que me gustaría compartir o estructurar para evidenciarlas de manera mas formal.

Muchas gracias por el apoyo, gracias por las observaciones y anotaciones dentro de los foros de discusión, siento que puedo seguir aprendiendo mas y es por eso que estoy agradecido por mis conocimientos adquiridos, los cuales siempre puedo retroalimentar viendo el curso nuevamente cada vez que lo considere pertinente.

By Maxwell Sarmento de Carvalho

Apr 09, 2019

One of the best courses ever! Plenty of things to learn, to evolve. Superb!

By LENDRICK ROBINSON

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. :-)

By Surya Pavan Malireddy

Apr 01, 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 Sooraj S

Mar 31, 2019

Good introduction to Machine Learning and implementation in Python.