Chevron Left
Вернуться к Applied Machine Learning in Python

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

4.6
звезд
Оценки: 4,817
Рецензии: 840

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

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!!

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

Фильтр по:

226–250 из 823 отзывов о курсе Applied Machine Learning in Python

автор: Dave C

Oct 25, 2019

Very enjoyable, informative and I really believe I can go on and build my own ML system with confidence. Recommended.

автор: SUDHAKAR M S

Oct 16, 2019

Great Course. Helped to understand the basics of machine learning, the algorithms and their applications using python.

автор: Pratyush L

Sep 28, 2018

The course gives a good overview of the concepts and a great paced programming assignments to understand the concepts.

автор: Emanuele P

Oct 25, 2017

It gives you the methods and the essential knowledge to build a learning pipeline using Python and SciKit-learn tools.

автор: Saiapin A

Jul 24, 2017

This is a great course for those who want to get acquainted with machine learning basics as well as its applications.

автор: bishnu m

May 27, 2018

I have increased my lots of machine learning skills specially with python language, I have got a very good practice.

автор: chris l

Jan 18, 2020

An excellent course if you are prepared to be patient and do lots of additional research outside the given content.

автор: Said G

Oct 26, 2019

It was really a good experience. The content is rich and clear and the tools at our disposal are of good quality.

автор: Dindayal H P

Jul 20, 2019

The overall course structure was very good. Also the instructor was good at his knowledge and explaination skill.

автор: Pooja C

Jun 17, 2018

Helped me understand the fundamental concepts and practice them with assignemens. I highly recommend this course.

автор: Janesh D

Nov 14, 2017

It was a great course. This course covered a lot of material and Professor explained every concepts very clearly.

автор: Yuwei Y

Jun 04, 2019

I like this course very much. It focuses on ML application and it's easy to understand. Definitely recommend it!

автор: Vasilis S

Aug 12, 2018

Great course! Assignment 4 is very interesting and allows you to apply all you've learnt in this course at once.

автор: Ryan J

Feb 11, 2018

Incredibly insightful and helpful for a recent master's graduate looking to augment his skills on the job market

автор: Matthias B

Aug 05, 2017

Great course, very hands-on. Maybe difficult to follow without any prior knowledge in machine learning, though.

автор: Liu L

Jan 03, 2019

This course provides a good introduction to using python in machine learning. It helps me to get hands on it.

автор: Mikhail S

Aug 27, 2017

Thank you for the very well done course! It's really helpful, has a clear explanation of topics and examples.

автор: Nitin k

Apr 22, 2019

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

автор: Mohamed A M A

Jan 19, 2019

The theoretical part is comprehensive with an excellent balance between the theory and practical exercises.

автор: HISHAM I A

Nov 05, 2018

Excellent collection of various types of Machine Learning Algorithms with visual demonstration and example.

автор: Rahul S

Dec 08, 2019

This course is Beautifully crafted to cover most of the important concepts of supervised machine learning.

автор: Christian E

Jan 19, 2019

Content and phase are very good. Very clear explanation of topic by the instructor. Appreciate it so much.

автор: Anurag W

Jul 18, 2019

This Course really provides great learning on Advance Machine learning techniques with Python application

автор: Matt E

Aug 29, 2017

Learned a lot in this course! Much better than the previous two and also taught by a different professor.

автор: Miguel Á B P

Jul 28, 2018

What a challenge. Incredible course, no words. Excellent pedagogy from professor Kevyn Collins-Thompson.