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2,814 Bewertungen

Über den Kurs

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

Top-Bewertungen

PM

Aug 19, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

SZ

Dec 20, 2016

Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

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2601 - 2625 von 2,730 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Kenny J

May 21, 2020

This course needs to be updated. It's hard to follow the notebooks since the lecture was on GraphLab, and some of the explanations were not elaborate enough, especially Week 6.

von Zein S

Jan 17, 2018

I like more to work with sklearn rather than GraphLab..

Actually many recommended this course to me, and I expect more excitement in the next courses in this specialization

von Eric.Wang

Mar 11, 2016

I don't like this course , because the homework can not match the lesson. I can not got more messages to completed the homework.

So I will Unregister this courser , Thanks.

von Morteza M

Nov 21, 2016

The only reason that I am giving 3 star is the design of the quizzes for each week. The readings are too long and the content of the quiz sometimes gets you frustrated!

von Chih W L

Sep 19, 2016

Professors are very good , i am really enjoy in this class, but no further discussion about implementing ML algorithm, just call the API to handle the sort of data.

von Zhongyi T

Mar 09, 2016

The lectures are fine. However the content is way too easy. Another course on Coursera `Mining Massive DataSets` is much better, in the depth and horizon.

von Fabio

Oct 07, 2018

App needed to complete assignments ceased to function early on - forum / admin did not help to find solution. Otherwise good intro to get started with ML.

von Deleted A

Jun 05, 2016

Generally ok. Towards the end of the course, the lectures could have been a bit more in depth - or provide students with a more in depth reading list.

von Kai W

Nov 21, 2015

I think this is an excellent course. I would have given 5 stars if this course is not based on Graphlab which is not affordable to the general public.

von Murat O

Jan 28, 2016

Gives a really broad overview of ML concepts. Examples (and assignments) use a commercial Dato product called (GraphLab Create). Expect nothing else.

von suresh k p

Jul 28, 2018

Nice explanation of basic ML but I would suggest please provide the practise tool with proper integration.That is a big headcahe in this course.

von Paul C

Nov 24, 2016

A solid course, let down by quality issues in the last two modules. I hope these are fixed soon because it would make this a top notch course...

von Jawahir M A K

Jul 18, 2020

It will give you an overview about the ML concept. But to get detail we need to have the specialization course or learn it our self.

von Kristoffer H

Jun 09, 2016

Get ready for a course that assumes you have all the software they use already installed without advanced notice or instructions!

von Abiodun M

Mar 18, 2018

Very good course; except the bugs in Graphlab with reference to .apply and lambda workers command . This needs to be fixed.....

von Corey K

Mar 11, 2016

All algorithms were black boxed. It was a nice course on how to use Dato's GraphLab and an overview of ML concepts.

von Michael B

Nov 02, 2015

Fun lectures but the coverage is too simplistic. Looking forward to the more in-depth courses in the specialization.

von Aleksei Z

Jan 16, 2020

Materials from video differ from the web ( in videos graphlab, in materials Turicreat), including home assignment.

von Ajay S

Mar 05, 2019

Good for beginner level, not for intermediate or advance level. I learned more about graphlab than anything else.

von Serban C S

Feb 11, 2018

Using a proprietary library for a paid course is not really a big issue but some people will be turned off by it.

von Pēteris K

Sep 23, 2017

Definitely a good intro to the richness of ML, but would have preferred more rigorous assignments and evaluation.

von Luca

Nov 10, 2016

not using scikit and assigment way too easy, not challenging, but high quality video, very easy to understand .

von Pubudu W

Jul 10, 2017

Good survey course on ML techniques. Not very detailed and the exercises are too simplistic for real learning.

von Nguyễn T T

Oct 14, 2015

the lectures are pretty great, engaging. the assignments stick with the lab exercise. the forum pretty active.

von ADNAN A G

Oct 09, 2020

old and bad quality but very good explanation half of the course is programming there is no machine learning.