Your goal is to create an image classifier that can distinguish between cats and dogs. For training purposes, you get a couple of animal images in your exercise files.
- [Instructor] Very soon,…we are going to create our own machine learning model…that can distinguish between cats and dogs.…To do so, we need to prepare a dataset…that we use to train our model,…and the dataset that we're going to use,…you will find that in your Exercise Files…in the Animal Images folder.…There you will find images that are already labeled…with either cat, in these cases,…or dog, and they are enumerated.…
What we need to do now is to copy all of these images…into its own folder in our virtual environment.…I've opened up the folder of my virtual environment,…machineLearningEnv.…In this folder, I'm going to create a new directory…or a new folder pressing Cmd + Shift + N on my keyboard…and I'm going to call that trainingData.…In this folder, I'm going to copy and paste all…of my images that you will find in your Animal Images folder…in your Exercise Files.…
This is the dataset that we are going to work with.…
Author
Brian Advent
Released
4/4/2018- Using Turi Create to create custom models
- Getting comfortable with Python
- Preparing data for Turi Create
- Creating a machine learning model with Turi Create
- Implementing an image picker controller
- Using Core ML and the Vision framework for image classification
Skill Level Advanced
Duration
Views
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Introduction
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Welcome1m 21s
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What you should know1m 6s
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1. Machine Learning: Basics and Tools
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Machine learning and Core ML5m 19s
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Your machine learning setup7m 22s
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2. Cats vs. Dogs: Create an ML Model
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The data set we work with1m 12s
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Work with Turi Create2m 56s
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3. Dogs vs. Cats: The iOS App
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Conclusion
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Next steps2m 4s
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Video: The data set we work with