Using BigML: Getting Hands-on with BigML
Machine Learning 2020
| Beginner
- 11 videos | 1h 16m 26s
- Includes Assessment
- Earns a Badge
BigML not only provides ease-of-use, but it also offers flexibility in how you work with your data. This course serves as a hands-on introduction to BigML and its vast array of features. You'll start by exploring the different ways data can be loaded into the platform and how these can be transformed into datasets to train and test a machine learning model. You'll gain practical experience with some of the tools available to help you better understand your data - from histograms and scatterplots to visualizations of value distribution. Moving on, you'll build a fundamental classification model, a decision tree, which takes employee details and predicts whether they'll stay or leave in the next year. Finally, you'll investigate some possible configurations for this model.
WHAT YOU WILL LEARN
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discover the key concepts covered in this course
recognize the features available in BigML to load data and train a machine learning model
load data from a variety of sources into BigML in order to train and evaluate machine learning models
organize your BigML resources into projects, such as data sources, datasets, and models
create a dataset out of a data source and analyze the different fields in the data
visualize relationships between various fields in a dataset -
split and sample a dataset, which can then be used to train and test a model
build a classification model that uses a decision tree and recognize how this performs classification
illustrate the process involved in performing classification when a decision tree model is used
customize a decision tree model when performing classification
summarize the key concepts covered in this course
IN THIS COURSE
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2m 32s
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8m 32s
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3. Loading Data into BigML8m 2s
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4. Creating a Project from BigML Resources9m
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5. Creating and Analyzing Datasets8m 45s
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6. Examining Relationships in Datasets9m 21s
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7. Transforming a Dataset7m 48s
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8. Building a Decision Tree Model8m 44s
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9. Analyzing a Decision Tree5m 58s
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10. Configuring a Decision Tree6m 9s
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11. Course Summary1m 37s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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