Back to Machine Learning Foundations: A Case Study Approach

Machine Learning Foundations: A Case Study Approach

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.

Status: Python Programming

Status: Machine Learning Algorithms

Course18 hours

Featured reviews

5.0

Reviewed Dec 19, 2016

Great course! Emily 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.

5.0

Reviewed Nov 13, 2016

Really liked the course and the teachers. Would have preferred more detail on the quizzes so I didn't feel as lost as I did some of the times while trying to piece together what a question meant.

5.0

Reviewed Jul 4, 2020

A very balanced first course that introduces machine learning in a very practical and simple way. I would recommend highly this course to anyone who plans to learn machine learning through practice.

5.0

Reviewed Sep 27, 2015

Excellent course, with really good lectures, material and assignment. Plus the professors are really amazing and their enthusiasm is really refreshing and makes the class more interesting. Loved it!

5.0

Reviewed Jun 4, 2017

This course is very helpful for people who are novice in machine learning. The course uses Graphlab Create which is different from scikit or R-libraries, but the tool(Graphlab) is excellent to use.

5.0

Reviewed Oct 16, 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

5.0

Reviewed Feb 14, 2016

With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!

5.0

Reviewed Dec 26, 2022

Amazing course, lots of great ideas and amazing instructors, i really enjoyed it and looking forward to see what's coming next in the specialization. Also i am really greatfull for this information

5.0

Reviewed Jun 8, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

5.0

Reviewed Jun 20, 2020

I'm very thankful to coursera. It's provide a cost of free certification of machine learning which cost in market is approximately 3000rs.i think coursera is a good platform. Thank you coursera.

5.0

Reviewed Nov 7, 2016

One of the best courses available online. Actually got to know how to apply theoretical knowledge in designing systems. You people are the best and made concepts and things really easy. Hats off!!

4.0

Reviewed May 18, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

All reviews

Showing: 20 of 3,164

Ravi

1.0

Reviewed Sep 8, 2018

The materials used in this course are extremely outdated. In order to access the data to do the projects you have to use SFrame, which is only supported up to Python 3.4.x. Python is currently on v 3.7.0. The data should be provided as .txt or .csv to be more universal. The instructors claim that you don't have to use a specific library to do this course, but you have to have at least SFrame in order to access the data! Further I am sure SFrame and Graphlab are good tools, but the course should be taught with open source tools so that the students can continue to use those tools after the course is over.

I wanted to like this course. I did enjoy the professor's teaching styles, but the fact that I would have to download a new outdated python environment, and non universally accepted tools, to even access the data is a major deal breaker!

Ibrahim

1.0

Reviewed Apr 29, 2017

My only happiest moment in this whole course is writing this review, I couldn't wait to finish it in order to give it the 1 star rating it deserved.

What I've seen from this course so far is abandonment , that's right this course is abandon ware, no questions get answered on the forums (asked a question a month ago and still didn't get an answer) and the links are outdated (links to further documentation don't work).

I wouldn't recommend this course to anyone wanting to learn Machine learning since the instructors use proprietary libraries that need a license to use outside this course thus application wise what you learn her isn't transferable only the conceptual content;however, even in that there isn't much content for, since everything is an introduction here so nothing is quite useful .

If your on a tight budget and your taking this specialization you could skip this course. Actually you could even skip this specialization since they canceled the capstone project so investing any money and time here is a waste. I can only recommend this specialization/course IF the instructors add a project at the end , be more involved on the forums , update non functional links ,and finally USE NON PROPRIETARY libraries hence they will need to take feedback from the students and redo most components of this specialization.

Oscar

1.0

Reviewed Oct 24, 2018

I spend two days trying to get the graphlap lib working on two OS, and could not. I had to spend couple of hours setting up the aws services to be able to work with the samples.

Phd's I dont think they make good teachers....

Thanks.

Jatin

1.0

Reviewed Mar 28, 2018

To follow along the course you need to install Graphlab library, which is the biggest challenge. Also, the support you get from the creators are not good enough.

I regret to waste my time on this course.

Sourav

1.0

Reviewed Jun 27, 2018

Too dependent on Sframes and graphlab which does not work most of the times. I had to spend an entire day just figuring out versions of python to make this work.

sreeraj

1.0

Reviewed Jan 21, 2018

Such a bad presentation with no help to people with graphiclab tool setup.

Andrew

1.0

Reviewed Nov 4, 2017

Requires software called Graphlab Create that would not install on my machine. Unable to complete any of the course material due to this.

Elvin

1.0

Reviewed Oct 26, 2017

The worse course I have ever taken on Coursera. Forcing you to use their own library which is also not open source and free is ridiculous! You will never use graphlab in the future and there are better alternatives available! Totally useless experience. And most of the time vide lectures are just some mumbo jumbo, like showing diapers or napkins for 2 minutes! I have successfully wasted a lot of time on this course.

Hernan

1.0

Reviewed Sep 25, 2017

I enrolled in this specialization to learn machine learning using GraphLab Create. Half way into the specialization the creators sold Turi, GrapLab's parent company, making it non available to the general public (not even by paying) and then all the knowledge devalued. I wish I had known this and I would have enrolled on a different specialization. The creators still give you the possibility of using numpy, scikit learn and pandas but I had already done a lot with GraphLab create. The time I invested on my nights after work became a waste. I was trying to convince the company I worked for to buy licenses for GraphLab create.

Coursera should not allow folks to create courses that promote a private license course because it would make people waste their time and money if they decide to privatize the software.

Don't take this course, and if you take it then only use GraphLab create when the authors give you no other option.

Teaching style: Carlos was good, Emily is not very clear and loses focus of the topics and often rambles. She seems very knowledgeable but she lacks clarity of exposition when compared to Carlos or Andrew Ng.

Gianmaria

2.0

Reviewed Jan 22, 2019

Very relevant material clearly explained by the professors, who are very knowledgeable and engageing. However the installation and usage of the GraphLab module is cumbersome and plagued with bugs. This could still work if there was enough support however I did not find any helpfrom the mentors/tutors who simply did not answer my questions in the Forum thus making my experience even more frustrating. Pity, I certainly hope Coursera can fix it as the class is quite good

Muhammad

5.0

Reviewed Jul 21, 2019

A great course, really designed to understand the underlying core concepts of machine learning using real-life examples which takes you through all that with little to no programming skills required!

Sharina

1.0

Reviewed Feb 9, 2019

I am extremely frustrated with this course. I have spent sooo many days just trying to get the software set up. It's currently week 3 and I can't complete week 1. I've followed the directions and run in numerous roadblocks, some of which I was able to resolve after searching through the course forums. I shouldn't have to scour the forums to get setup...the instructions should be updated. Unfortunately, I'm still stuck in week 1, unable to get the software running properly. It's really frustrating.

strx

1.0

Reviewed Apr 12, 2017

Maybe a good course, but you need to be an IT crack to be able to install the software and make it works. Online help does not help. Irritating! 45USD lost. I don't recommend this course.

Rahul

1.0

Reviewed Dec 23, 2017

Course uses proprietary packages. Better learning from "The Analytics Edge" conducted by MIT at Edx.org

Walther

1.0

Reviewed Jul 2, 2018

relying on proprietary library and unreliable notebook made this experience painful

Matthew

1.0

Reviewed Oct 26, 2017

I just completed the first week of this course and am choosing not to continue. The first week consisted of 75 minutes of video in which we learned a half dozen facts regarding Python syntax and the use of SFrames. This content could have been presented in a single 5 minute video with just a little planning and editing. I realize that the presenters perhaps wanted to ease folks in, but this is silly. There may be good content in the following weeks, but I am not patient enough to find out. Gonna try a different ML class. Sorry guys.

lianghui

1.0

Reviewed Mar 9, 2019

the graphlab can not be installed

Mike

1.0

Reviewed Jun 14, 2016

The course is basically an advertisement for the software one of the teachers created. I did learn a bit of high level concepts, but when it comes to coding, the answers is always 'conveniently, my software does this for you'. I wanted to actually learn about these concepts deeper, and implement them.

I also was able to complete this 6 week paid course in a few days which should not be possible. I have since started the free Stanford course taught by a co-founder of coursera, and it is MUCH better! I recommend it to anyone!

Eugene

1.0

Reviewed Feb 10, 2017

If you are considering this specialization I would recommend the Andrew Ng course instead and the main reason is that it isn't depend on proprietary ML framework. Despite the good lectures, the assignments don't help you develop the knowledge required for ML developer role.

Taking in consideration the permanent postponing the courses delivery, from summer 2016 to summer 2017, finally the most interesting part of the specialization was cancelled. I'm completely disappointed with the specialization learning expirience.

Theron

1.0

Reviewed Nov 4, 2017

Good intro to the ML concepts, but my review is negative due to :