Model Management: Building Machine Learning Models & Pipelines
Machine Learning
| Intermediate
- 11 Videos | 31m
- Includes Assessment
- Earns a Badge
In this course, you will explore various approaches to building and implementing machine learning (ML) models and pipelines and will learn how to manage classification and regression problems. Begin this 11-video course by taking a look at the differences between ML models and ML algorithms. You will go on to learn about the different types of ML models and will then explore the approaches to developing and building them. Discover how to create and save ML models by using scikit-learn, and learn to recognize the various models that can be used to manage classification and regression problems. Explore how to build ML pipelines and then examine the prominent tools that can be used. You will learn how to implement scikit-learn ML pipelines, and in the final tutorial, learners will recall the steps involved in iterative machine learning model management and the associated benefits. In the concluding exercise, you will be asked to build ML models and pipelines by using scikit-learn.
WHAT YOU WILL LEARN
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recognize the differences between machine learning models and algorithmsidentify the different types of machine learning modelsdescribe the approaches and steps involved in developing machine learning modelscreate and save machine learning models using scikit-learnlist machine learning models that can be used to manage classification and regression problems
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build machine learning pipelineslist prominent tools that can be used to build machine learning pipelinesimplement machine learning pipelines using scikit-learnrecall the steps involved in iterative machine learning model management and the associated benefitsbuild machine learning models and pipelines using scikit-learn
IN THIS COURSE
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1.Course Overview1m 37sUP NEXT
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2.Machine Learning Algorithms and Models4m 17s
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3.Machine Learning Model Types2m 1s
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4.Machine Learning Model Development2m 39s
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5.Creating and Saving ML Models with scikit-learn3m 31s
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6.Models for Regression and Classification Management3m 40s
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7.Building Machine Learning Pipelines2m 30s
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8.Machine Learning Pipeline Tools2m 53s
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9.Machine Learning Pipeline Implementation3m 26s
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10.Iterative Machine Learning Model2m 24s
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11.Exercise: Build Machine Learning Models & Pipelines2m 2s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion of this course, which can be shared on any social network or business platform
Digital badges are yours to keep, forever.