LINKEDIN LEARNING Applied Machine Learning: Algorithms

LINKEDIN LEARNING Applied Machine Learning: Algorithms

LINKEDIN LEARNING APPLIED MACHINE ALGORITHMS-BiFiSO
English | Size: 348.97 MB
Category: Tutorial

What you'll learn
Models vs. algorithms
Cleaning continuous and categorical variables
Tuning hyperparameters
Pros and cons of logistic regression
Fitting a support vector machines model
When to consider using a multilayer perceptron model
Using the random forest algorithm
Fitting a basic boosting model
In the first installment of the Applied Machine Learning series, instructor Derek Jedamski covered foundational concepts, providing you with a general recipe to follow to attack any machine learning problem in a pragmatic, thorough manner. In this course-the second and final installment in the series-Derek builds on top of that architecture by exploring a variety of algorithms, from logistic regression to gradient boosting, and showing how to set a structure that guides you through picking the best one for the problem at hand. Each algorithm has its pros and cons, making each one the preferred choice for certain types of problems. Understanding what actually drives each algorithm, as well as their benefits and drawbacks, can give you a significant competitive advantage as a data scientist.
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The Complete Self-Driving Car Course - Applied Deep Learning (Updated) .

The Complete Self-Driving Car Course - Applied Deep Learning (Updated) .

The Complete Self-Driving Car Course - Applied Deep Learning (2019)
WEBRip | English | MP4 + Project files | 1280 x 720 | AVC ~1237 Kbps | 30 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | 18:04:51 | 9.49 GB
Genre: Video Tutorial

Learn to use Deep Learning, Computer Vision and Machine Learning techniques to Build an Autonomous Car with Python
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Linkedin Learning Applied Machine Learning Algorithms-XCODE

Linkedin Learning Applied Machine Learning Algorithms-XCODE

Linkedin Learning Applied Machine Learning Algorithms-XCODE
English | Size: 346.31 MB
Category: Tutorial

In the first installment of the Applied Machine Learning series, instructor Derek Jedamski covered foundational concepts, providing you with a general recipe to follow to attack any machine learning problem in a pragmatic, thorough manner. In this course-the second and final installment in the series-Derek builds on top of that architecture by exploring a variety of algorithms, from logistic regression to gradient boosting, and showing how to set a structure that guides you through picking the best one for the problem at hand. Each algorithm has its pros and cons, making each one the preferred choice for certain types of problems. Understanding what actually drives each algorithm, as well as their benefits and drawbacks, can give you a significant competitive advantage as a data scientist.
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Applied Machine Learning Algorithms .

Applied Machine Learning Algorithms .

Applied Machine Learning: Algorithms
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 345 MB
Genre: eLearning | Language: English

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The Complete Self-Driving Car Course - Applied Deep Learning


The Complete Self-Driving Car Course - Applied Deep Learning
The Complete Self-Driving Car Course - Applied Deep Learning
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 17 Hours 40M | 3.99 GB
Genre: eLearning | Language: English

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The Complete Self-Driving Car Course - Applied Deep Learning .

The Complete Self-Driving Car Course - Applied Deep Learning .

The Complete Self-Driving Car Course - Applied Deep Learning
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 17 Hours 40M | 3.99 GB
Genre: eLearning | Language: English

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Applied Computing and Information Technology


Applied Computing and Information Technology

Roger Lee - Applied Computing and Information Technology
Published: 2017-03-15 | ISBN: 3319514717 | PDF | 197 pages | 5.61 MB

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Advanced Mechanics of Materials and Applied Elasticity (6th Edition) [Early Release]


Advanced Mechanics of Materials and Applied Elasticity (6th Edition) [Early Release]

Advanced Mechanics of Materials and Applied Elasticity (6th Edition) (Prentice Hall International Series in the Physical and Chemical Engineering Sciences)
by Ansel C. Ugural

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Proceedings of the Conference on Applied Mathematics and Scientific Computing


Proceedings of the Conference on Applied Mathematics and Scientific Computing

Zlatko Drmac, Miljenko Marusic, Zvonimir Tutek, "Proceedings of the Conference on Applied Mathematics and Scientific Computing"
English | 2005 | ISBN: 1402031963 | PDF | pages: 353 | 13.6 mb

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Introduction to the Foundations of Applied Mathematics


Introduction to the Foundations of Applied Mathematics

Mark H. Holmes - Introduction to the Foundations of Applied Mathematics
Published: 2009-07-01 | ISBN: 0387877495, 1461417139 | PDF + DJVU | 468 pages | 12.12 MB

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