課程信息
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第 2 門課程(共 4 門)

100% 在線

立即開始,按照自己的計劃學習。

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完成時間大約為13 小時

建議:4 weeks of study, 6-8 hours/week...

英語(English)

字幕:英語(English), 韓語

您將獲得的技能

Random ForestPredictive AnalyticsMachine LearningR Programming

第 2 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13 小時

建議:4 weeks of study, 6-8 hours/week...

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 2 小時

Practical Statistical Inference

Learn the basics of statistical inference, comparing classical methods with resampling methods that allow you to use a simple program to make a rigorous statistical argument. Motivate your study with current topics at the foundations of science: publication bias and reproducibility.

...
28 個視頻 (總計 121 分鐘)
28 個視頻
Hypothesis Testing5分鐘
Significance Tests and P-Values3分鐘
Example: Difference of Means4分鐘
Deriving the Sampling Distribution6分鐘
Shuffle Test for Significance4分鐘
Comparing Classical and Resampling Methods3分鐘
Bootstrap6分鐘
Resampling Caveats6分鐘
Outliers and Rank Transformation3分鐘
Example: Chi-Squared Test3分鐘
Bad Science Revisited: Publication Bias4分鐘
Effect Size4分鐘
Meta-analysis5分鐘
Fraud and Benford's Law4分鐘
Intuition for Benford's Law2分鐘
Benford's Law Explained Visually3分鐘
Multiple Hypothesis Testing: Bonferroni and Sidak Corrections3分鐘
Multiple Hypothesis Testing: False Discovery Rate4分鐘
Multiple Hypothesis Testing: Benjamini-Hochberg Procedure3分鐘
Big Data and Spurious Correlations4分鐘
Spurious Correlations: Stock Price Example3分鐘
How is Big Data Different?3分鐘
Bayesian vs. Frequentist4分鐘
Motivation for Bayesian Approaches3分鐘
Bayes' Theorem2分鐘
Applying Bayes' Theorem4分鐘
Naive Bayes: Spam Filtering4分鐘
2
完成時間為 2 小時

Supervised Learning

Follow a tour through the important methods, algorithms, and techniques in machine learning. You will learn how these methods build upon each other and can be combined into practical algorithms that perform well on a variety of tasks. Learn how to evaluate machine learning methods and the pitfalls to avoid.

...
26 個視頻 (總計 111 分鐘), 1 個閱讀材料, 1 個測驗
26 個視頻
Simple Examples3分鐘
Structure of a Machine Learning Problem5分鐘
Classification with Simple Rules5分鐘
Learning Rules4分鐘
Rules: Sequential Covering3分鐘
Rules Recap2分鐘
From Rules to Trees2分鐘
Entropy4分鐘
Measuring Entropy4分鐘
Using Information Gain to Build Trees6分鐘
Building Trees: ID3 Algorithm2分鐘
Building Trees: C.45 Algorithm4分鐘
Rules and Trees Recap3分鐘
Overfitting7分鐘
Evaluation: Leave One Out Cross Validation5分鐘
Evaluation: Accuracy and ROC Curves5分鐘
Bootstrap Revisited4分鐘
Ensembles, Bagging, Boosting4分鐘
Boosting Walkthrough5分鐘
Random Forests3分鐘
Random Forests: Variable Importance5分鐘
Summary: Trees and Forests2分鐘
Nearest Neighbor4分鐘
Nearest Neighbor: Similarity Functions4分鐘
Nearest Neighbor: Curse of Dimensionality3分鐘
1 個閱讀材料
R Assignment: Classification of Ocean Microbes10分鐘
1 個練習
R Assignment: Classification of Ocean Microbes28分鐘
3
完成時間為 1 小時

Optimization

You will learn how to optimize a cost function using gradient descent, including popular variants that use randomization and parallelization to improve performance. You will gain an intuition for popular methods used in practice and see how similar they are fundamentally.

...
11 個視頻 (總計 41 分鐘)
11 個視頻
Gradient Descent Visually4分鐘
Gradient Descent in Detail2分鐘
Gradient Descent: Questions to Consider3分鐘
Intuition for Logistic Regression4分鐘
Intuition for Support Vector Machines3分鐘
Support Vector Machine Example3分鐘
Intuition for Regularization3分鐘
Intuition for LASSO and Ridge Regression3分鐘
Stochastic and Batched Gradient Descent5分鐘
Parallelizing Gradient Descent3分鐘
4
完成時間為 2 小時

Unsupervised Learning

A brief tour of selected unsupervised learning methods and an opportunity to apply techniques in practice on a real world problem.

...
4 個視頻 (總計 21 分鐘), 1 個測驗
4 個視頻
K-means5分鐘
DBSCAN4分鐘
DBSCAN Variable Density and Parallel Algorithms4分鐘
4.1
53 個審閱Chevron Right

25%

完成這些課程後已開始新的職業生涯

20%

通過此課程獲得實實在在的工作福利

來自实用预测分析:模型与方法的熱門評論

創建者 SPDec 23rd 2016

Fantastic course! Excellent conceptual teaching for people who already know the subject but need some more clarity on how to approach statistical tests and machine learning.

創建者 KPFeb 8th 2016

I enjoy this course. The delivery and the course topics were very interesting. I learnt a lot and peer reviewing other people assignments is a great learning opportunity .

講師

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Bill Howe

Director of Research
Scalable Data Analytics

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 大规模数据科学 專項課程

Learn scalable data management, evaluate big data technologies, and design effective visualizations. This Specialization covers intermediate topics in data science. You will gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts. You will also learn to visualize data and communicate results, and you’ll explore legal and ethical issues that arise in working with big data. In the final Capstone Project, developed in partnership with the digital internship platform Coursolve, you’ll apply your new skills to a real-world data science project....
大规模数据科学

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