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Machine Learning Mastery With Weka.pdf
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Machine Learning Mastery With Weka 14-day Mini-course
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Jason Brownlee
Machine Learning Mastery With Weka
14 Day Mini-Course
Contents
Before We Get Started... 1
Lesson 01: Download and Install Weka 4
Lesson 02: Load Standard Machine Learning Datasets 5
Lesson 03: Descriptive Stats and Visualization 6
Lesson 04: Normalize and Standardize Your Data 7
Lesson 05: Perform Feature Selection on Your Data 8
Lesson 06: Machine Learning Algorithms in Weka 9
Lesson 07: Estimate Model Performance 10
Lesson 08: Baseline Performance On Your Data 11
Lesson 09: Tour of Classification Algorithms 12
Lesson 10: Tour of Regression Algorithms 13
Lesson 11: Tour of Ensemble Algorithms 14
Lesson 12: Compare the Performance of Algorithms 15
Lesson 13: Tune Algorithm Parameters 16
Lesson 14: Save Your Model 17
Final Word Before You Go... 18
ii
Before We Get Started...
Machine learning is a fascinating study, but how do you actually use it on your own problems?
You may be confused as to how best prepare your data for machine learning, which algorithms
to use or how to choose one model over another. In this guide you will discover a 14-part crash
course into applied machine learning using the Weka platform without a single mathematical
equation or line of programming code.
After completing this mini course:
You will know how to work through a dataset end-to-end and deliver a set of predictions
or a high performance model.
You will know your way around the Weka machine learning workbench including how to
explore algorithms and design controlled experiments.
You will know how to create multiple views of your problem, evaluate multiple algorithms
and use statistics to choose the best performing model for your own predictive modeling
problems.
Let’s get started.
This is a long and useful guide. You might want to print it out.
Who Is This Mini-Course For?
Before we get started, let’s make sure you are in the right place. The list below provides some
general guidelines as to who this course was designed for. Don’t panic if you don’t match these
points exactly, you might just need to brush up in one area or another to keep up.
You are a developer that knows a little machine learning. This means you know about some
of the basics of machine learning like cross validation, some algorithms and the bias-variance
trade-off. It does not mean that you are a machine learning PhD, just that you know the
landmarks or know where to look them up.
This mini-course is not a textbook on machine learning. It will take you from a developer
that knows a little machine learning to a developer who can use the Weka platform to work
through a dataset from beginning to end and deliver a set of predictions or a high performance
model.
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