Chevron Left
Retour à Machine Learning Foundations: A Case Study Approach

Avis et commentaires pour d'étudiants pour Machine Learning Foundations: A Case Study Approach par Université de Washington

13,101 évaluations

À propos du cours

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....

Meilleurs avis


19 déc. 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.


18 août 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

Filtrer par :

176 - 200 sur 3,049 Avis pour Machine Learning Foundations: A Case Study Approach

par Dave G

17 déc. 2021

par Louis U

15 nov. 2017

par Syed M Z H K

5 août 2017

par Prachur B

27 déc. 2016

par Aman M

18 déc. 2018

par Tobi L

6 déc. 2015

par Aleksander S

1 févr. 2019

par George C

26 déc. 2015

par Chengcheng L

27 déc. 2015

par Evan S

11 mars 2019

par Divyansh S

25 déc. 2018

par Matthew S

7 janv. 2020

par Dhananjay M

7 févr. 2016

par Allen C L

17 juin 2016

par Christopher M

6 déc. 2018

par Joseph C

5 déc. 2015

par Mitkumar P

27 août 2017

par Siddharth M

18 déc. 2015

par Ferenc F P

10 janv. 2018

par Parag K

23 mai 2021

par Sauvage F

18 déc. 2015

par Christine S

9 nov. 2015

par Christopher O

2 juin 2017


11 avr. 2016

par jackytu256

15 déc. 2015