Segment 5 - Get the Tools - Machine Learning | Coursera

Segment 5 - Get the Tools

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コロラド大学ボルダー校（University of Colorado Boulder）

Project Planning and Machine Learning

コロラド大学ボルダー校（University of Colorado Boulder）

4.7 (93 件の評価)

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6.5K人の学生が登録しました

Developing Industrial Internet of Things 専門講座における 3 の 2 コース

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This course can also be taken for academic credit as ECEA 5386, part of CU Boulder’s Master of Science in Electrical Engineering degree. This is part 2 of the specialization. In this course students will learn : * How to staff, plan and execute a project * How to build a bill of materials for a product * How to calibrate sensors and validate sensor measurements * How hard drives and solid state drives operate * How basic file systems operate, and types of file systems used to store big data * How machine learning algorithms work - a basic introduction * Why we want to study big data and how to prepare data for machine learning algorithms

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4.7 (93 件の評価)

5 stars
77.41%
4 stars
15.05%
3 stars
4.30%
2 stars
2.15%
1 star
1.07%

DB

2020年7月6日

Very well designed and delivered Course. Thank you for the opportunity. Special Thanks to Prof Dave Sluiter

AN

2020年6月2日

It was a good course to get a background and basic clearing while developing IIoT projects...

レッスンから

Machine Learning

Introduction0:30

Segment 1 - Learning Outcomes1:35

Segment 2 - AI Backgrounder6:59

Segment 3 - Machine Learning, What is it?6:34

Segment 4 - Machine Learning Schools of Thought9:33

Segment 5 - Get the Tools3:20

Segment 6 - Categories of Machine Learning5:04

Segment 7 - Supervised Learning, Linear Regression 17:56

Segment 8 - Supervised Learning, Linear Regression 29:47

Segment 9 - Supervised Learning, Linear Regression 38:28

Segment 10 - Supervised Learning, Linear Regression 49:10

Segment 11 - Supervised Learning, Bayes Theorem4:38

Segment 12 - Supervised Learning, Naive Bayes9:53

Segment 13 - Supervised Learning, Support Vector Machines (SVM) Introduction0:55

Segment 14 - Supervised Learning, SVMs12:12

Segment 15 - Unsupervised Learning, K-Means11:24

Segment 16 - Reinforcement Learning0:46

Segment 17 - Supervised Learning, Deep Learning2:32

Segment 18 - Rick Rashid, Natural Language Processing8:36

Segment 19 - Deep Learning, Hearing Aid2:38

Segment 20 - Machine Learning in IIoT4:53

Segment 21 - Machine Learning Summary4:07

講師

David Sluiter
Professor Adjunct

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