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Practical Machine Learning: Real World Projects,Case Studies

Solve business problems using data science, machine learning practically and build projects using python. [Set3]
Instructor:
Pianalytix .
3,532 students enrolled
English [Auto]
Build machine learning models
Exploratory data analysis
Feature engineering
Feature Selection

In this tutorial, you will discover how to develop and evaluate a model for the imbalanced adult income classification dataset.

After completing this tutorial, you will know:

  • How to load and explore the dataset and generate ideas for data preparation and model selection.

  • How to systematically evaluate a suite of machine learning models with a robust test harness.

  • How to fit a final model and use it to predict class labels for specific cases.

Many binary classification tasks do not have an equal number of examples from each class, e.g. the class distribution is skewed or imbalanced.

A popular example is the adult income dataset that involves predicting personal income levels as above or below $50,000 per year based on personal details such as relationship and education level. There are many more cases of incomes less than $50K than above $50K, although the skew is not severe.

You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Includes

3 hours on-demand video
4 articles
Full lifetime access
Access on mobile and TV
Certificate of Completion
Practical Machine Learning: Real World Projects,Case Studies
Price:
$68.98 $52

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