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

4.6
étoiles
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

PM

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.

SZ

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.

Filtrer par :

2651 - 2675 sur 3,049 Avis pour Machine Learning Foundations: A Case Study Approach

par Divya v M

28 mai 2016

par Jorge S N

9 avr. 2016

par HARSHIT J

7 juin 2020

par Bhakthavatsala R

16 juin 2018

par Fenjin W

15 avr. 2016

par Prashant D

16 juin 2020

par Yagyansh S K

2 déc. 2016

par Mitali C

10 juin 2020

par Avinash P M

13 déc. 2016

par Alvin B K

17 août 2020

par 吴青

6 déc. 2017

par Albert Z

6 févr. 2016

par Omar H F A

3 juil. 2020

par Gopinath T

14 mai 2019

par Sam P

16 janv. 2018

par Qishen S

25 mai 2017

par Harsh R

18 mai 2020

par shadab h

18 nov. 2018

par Deleted A

21 janv. 2019

par Spike Y

30 nov. 2017

par Abid A S

3 août 2017

par Amilkar A H M

10 mai 2019

par Roberto E

28 nov. 2016

par Matic D B

9 févr. 2016

par Jayant S

22 oct. 2019