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返回到 机器学习基础:案例研究

學生對 华盛顿大学 提供的 机器学习基础:案例研究 的評價和反饋

12,183 個評分
2,916 條評論


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....



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.


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.


2401 - 机器学习基础:案例研究 的 2425 個評論(共 2,826 個)

創建者 Jay D S


this course should include some more coding about python in manchine learning and knn

創建者 Ibrahim G


it's very cool base and i hope next specialization course will get more into details.

創建者 Deleted A


The first week was a little chatty but the content of the rest of the weeks is good.

創建者 Chin-Teng H


bomb bad awful interest present immutable sad great time tack how hungry hungry opps

創建者 Hakim L


Good course despite the technical issues with GraphLab Create in Coursera Notebook.

創建者 张宸恺


Good on presenting and using ML tools, but the part of principle is not good enough

創建者 Mateusz B R P S z o o N D 3 0 W


I enjoyed this course but I think assignments could be a little bit more difficult.

創建者 Satyam R


Thanks a lot for providing such intuitive approach towards the ML and DL Concepts.

創建者 Kim K


a very good introduction for machine learning with good examples and explainations

創建者 Shyam A


good, But check whether your pc can run on graphlab before taking up this course.

創建者 Sachin R G


Need some improvement like much more focus on statistical concepts behind program

創建者 Shashikant K


This is very good course. This is helpful for me. Some problem on using graphlab.

創建者 Anurag G


Preety good course but instead of Sframe , i prefer pandas and sklearn libraries

創建者 Durga P S


Very nice foundation course in Machine Learning especially with GraphLab create.

創建者 Henrik


Very nice content but dont like we use graphlab since i wont use it after course

創建者 vivekanandhan


Last module on Deep learning is not explained well as compared to other modules.

創建者 Xun Y


great introductory course to machine learning, includes almost all the aspects.

創建者 Zynab S


very good for one who has no idea about machine learning , but I dont like dato

創建者 Bruno C K


very nice! A little bit more of reading material would be interesting, though..



hands on material is overly simplified perhaps because it is foundation course

創建者 Ankita S


Great course !! With practical knowledge and the trending topics are captured.

創建者 Mrutyunjaya S Y


It given more understanding of all concepts..Its really helpfull for beginners

創建者 mikhil i


The deep learning part of the course needs to be better done. The rest is good

創建者 Ricky W


Very nice introduction to Machine Learning and to Python programming language

創建者 Daniel B S d S


The course is great, but it would be greater if used open source free tools.