課程信息
203,704 次近期查看

第 1 門課程(共 4 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為24 小時

建議:6 weeks of study, 5-8 hours/week...

英語(English)

字幕:英語(English), 韓語, 越南語, 中文(簡體)

您將獲得的技能

Python ProgrammingMachine Learning ConceptsMachine LearningDeep Learning

第 1 門課程(共 4 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為24 小時

建議:6 weeks of study, 5-8 hours/week...

英語(English)

字幕:英語(English), 韓語, 越南語, 中文(簡體)

學習Course的學生是

  • Machine Learning Engineers
  • Data Scientists
  • Data Analysts
  • Risk Managers
  • Technical Leads

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

Welcome

18 個視頻 (總計 84 分鐘), 8 個閱讀材料, 1 個測驗
18 個視頻
Who we are5分鐘
Machine learning is changing the world3分鐘
Why a case study approach?7分鐘
Specialization overview6分鐘
How we got into ML3分鐘
Who is this specialization for?4分鐘
What you'll be able to do57
The capstone and an example intelligent application6分鐘
The future of intelligent applications2分鐘
Starting a Jupyter Notebook5分鐘
Creating variables in Python7分鐘
Conditional statements and loops in Python8分鐘
Creating functions and lambdas in Python3分鐘
Starting Turi Create & loading an SFrame4分鐘
Canvas for data visualization4分鐘
Interacting with columns of an SFrame4分鐘
Using .apply() for data transformation5分鐘
8 個閱讀材料
Important Update regarding the Machine Learning Specialization10分鐘
Slides presented in this module10分鐘
Getting started with Python, Jupyter Notebook, & Turi Create10分鐘
Where should my files go?10分鐘
Important changes from previous courses10分鐘
Download the Jupyter Notebook used in this lesson to follow along10分鐘
Download the Jupyter Notebook used in this lesson to follow along10分鐘
Download Wiki People Data10分鐘
1 個練習
SFrames15分鐘
2
完成時間為 2 小時

Regression: Predicting House Prices

19 個視頻 (總計 82 分鐘), 3 個閱讀材料, 2 個測驗
19 個視頻
What is the goal and how might you naively address it?3分鐘
Linear Regression: A Model-Based Approach5分鐘
Adding higher order effects4分鐘
Evaluating overfitting via training/test split6分鐘
Training/test curves4分鐘
Adding other features2分鐘
Other regression examples3分鐘
Regression ML block diagram5分鐘
Loading & exploring house sale data7分鐘
Splitting the data into training and test sets2分鐘
Learning a simple regression model to predict house prices from house size3分鐘
Evaluating error (RMSE) of the simple model2分鐘
Visualizing predictions of simple model with Matplotlib4分鐘
Inspecting the model coefficients learned1分鐘
Exploring other features of the data6分鐘
Learning a model to predict house prices from more features3分鐘
Applying learned models to predict price of an average house5分鐘
Applying learned models to predict price of two fancy houses7分鐘
3 個閱讀材料
Slides presented in this module10分鐘
Download the Jupyter Notebook used in this lesson to follow along10分鐘
Predicting house prices assignment10分鐘
2 個練習
Regression18分鐘
Predicting house prices6分鐘
3
完成時間為 2 小時

Classification: Analyzing Sentiment

19 個視頻 (總計 75 分鐘), 3 個閱讀材料, 2 個測驗
19 個視頻
What is an intelligent restaurant review system?4分鐘
Examples of classification tasks4分鐘
Linear classifiers5分鐘
Decision boundaries3分鐘
Training and evaluating a classifier4分鐘
What's a good accuracy?3分鐘
False positives, false negatives, and confusion matrices6分鐘
Learning curves5分鐘
Class probabilities1分鐘
Classification ML block diagram3分鐘
Loading & exploring product review data2分鐘
Creating the word count vector2分鐘
Exploring the most popular product4分鐘
Defining which reviews have positive or negative sentiment4分鐘
Training a sentiment classifier3分鐘
Evaluating a classifier & the ROC curve4分鐘
Applying model to find most positive & negative reviews for a product4分鐘
Exploring the most positive & negative aspects of a product4分鐘
3 個閱讀材料
Slides presented in this module10分鐘
Download the Jupyter Notebook used in this lesson to follow along10分鐘
Analyzing product sentiment assignment10分鐘
2 個練習
Classification14分鐘
Analyzing product sentiment22分鐘
4
完成時間為 2 小時

Clustering and Similarity: Retrieving Documents

17 個視頻 (總計 76 分鐘), 3 個閱讀材料, 2 個測驗
17 個視頻
What is the document retrieval task?1分鐘
Word count representation for measuring similarity6分鐘
Prioritizing important words with tf-idf3分鐘
Calculating tf-idf vectors5分鐘
Retrieving similar documents using nearest neighbor search2分鐘
Clustering documents task overview2分鐘
Clustering documents: An unsupervised learning task4分鐘
k-means: A clustering algorithm3分鐘
Other examples of clustering6分鐘
Clustering and similarity ML block diagram7分鐘
Loading & exploring Wikipedia data5分鐘
Exploring word counts5分鐘
Computing & exploring TF-IDFs7分鐘
Computing distances between Wikipedia articles5分鐘
Building & exploring a nearest neighbors model for Wikipedia articles3分鐘
Examples of document retrieval in action4分鐘
3 個閱讀材料
Slides presented in this module10分鐘
Download the Jupyter Notebook used in this lesson to follow along10分鐘
Retrieving Wikipedia articles assignment10分鐘
2 個練習
Clustering and Similarity12分鐘
Retrieving Wikipedia articles18分鐘
4.6
2159 個審閱Chevron Right

33%

完成這些課程後已開始新的職業生涯

30%

通過此課程獲得實實在在的工作福利

來自机器学习基础:案例研究的熱門評論

創建者 SZDec 20th 2016

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.

創建者 PMAug 19th 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.

講師

Avatar

Carlos Guestrin

Amazon Professor of Machine Learning
Computer Science and Engineering
Avatar

Emily Fox

Amazon Professor of Machine Learning
Statistics

關於 华盛顿大学

Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world....

關於 机器学习 專項課程

This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data....
机器学习

常見問題

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

還有其他問題嗎?請訪問 學生幫助中心