Chevron Left
Zurück zu Machine Learning Foundations: A Case Study Approach

Kursteilnehmer-Bewertung und -Feedback für Machine Learning Foundations: A Case Study Approach von University of Washington

11,698 Bewertungen
2,801 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....



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.


Oct 17, 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

Filtern nach:

2476 - 2500 von 2,717 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Waquar R

Aug 09, 2016

this is really good

von Vivek A

Apr 19, 2016

Enjoyed this class.

von Fei F

Dec 22, 2015

Easy for beginners.

von Joydev H

Nov 15, 2019

Awesome Experience

von Binil K

Jan 10, 2016

Really great one!!

von Quang H N

Dec 28, 2015

Good for ML newbie

von amit d

Feb 04, 2020

nice explaination


Jan 05, 2020

Very nice program


Jul 05, 2020

more informative

von Oscar M

May 29, 2016

Very insightfull

von Tulasi P D

Jul 15, 2020

it is so useful

von Rohith m

Apr 17, 2020

very intersting

von shane

Oct 22, 2015

Very practical.

von Rohit K S

Sep 30, 2020

Good Course!!

von Divyashree

Sep 14, 2020

A good course

von Rupali G

Nov 02, 2017

good content

von André G

May 14, 2016

Good course.

von 廖敏宏

Sep 24, 2020

Very useful


Sep 18, 2020



Jul 19, 2020

Good course

von Shubham D

Dec 03, 2016

nice course

von Le H P

Aug 16, 2019

well done!

von Daniel Ø

Jan 18, 2016

very basic

von Sayam N

Sep 25, 2020


von Aishwarya S

Jul 05, 2020

very nice