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 algorithms
identify the different types of machine learning models
describe the approaches and steps involved in developing machine learning models
create and save machine learning models using scikit-learn
list machine learning models that can be used to manage classification and regression problems -
build machine learning pipelines
list prominent tools that can be used to build machine learning pipelines
implement machine learning pipelines using scikit-learn
recall the steps involved in iterative machine learning model management and the associated benefits
build machine learning models and pipelines using scikit-learn
IN THIS COURSE
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1m 37s
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4m 17sAfter completing this video, you will be able to recognize the differences between machine learning models and algorithms. FREE ACCESS
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3. Machine Learning Model Types2m 1sIn this video, you will learn how to identify the different types of machine learning models. FREE ACCESS
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4. Machine Learning Model Development2m 39sUpon completion of this video, you will be able to describe the approaches and steps involved in developing machine learning models. FREE ACCESS
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5. Creating and Saving ML Models with scikit-learn3m 31sDuring this video, you will learn how to create and save machine learning models using the scikit-learn library. FREE ACCESS
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6. Models for Regression and Classification Management3m 40sUpon completion of this video, you will be able to list machine learning models that can be used to manage classification and regression problems. FREE ACCESS
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7. Building Machine Learning Pipelines2m 30sFind out how to build machine learning pipelines. FREE ACCESS
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8. Machine Learning Pipeline Tools2m 53sAfter completing this video, you will be able to list prominent tools that can be used to build machine learning pipelines. FREE ACCESS
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9. Machine Learning Pipeline Implementation3m 26sIn this video, find out how to implement machine learning pipelines using scikit-learn. FREE ACCESS
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10. Iterative Machine Learning Model2m 24sAfter completing this video, you will be able to recall the steps involved in iterative machine learning model management and the benefits associated with it. FREE ACCESS
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11. Exercise: Build Machine Learning Models & Pipelines2m 2sIn this video, you will learn how to build machine learning models and pipelines using the scikit-learn library. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.
