To convert an existing machine learning model, you need to use Python. In order to have a protected environment, use a tool called virtualenv. This is a tool that creates an isolated Python environment for each of your projects. For a particular project, instead of installing required packages globally, it is best to install them in an isolated folder in the project, that will be managed by virtualenv.
- [Instructor] We have already created…a cool machine learning app that can determine…the gender by inputting a name into it…and then determining the gender based on that name.…If you have looked through the models…that were provided by Apple, then you…might have seen that the model…that we used wasn't provided there.…So, we can indeed use other machine learning models…that were already created and converted…into our machine learning model format…that we need for Xcode.…
If you have a look at the machine learning website…from Apple, then you will also find…the so called Core ML Tools and, if we get…the Core ML tools, and we can download them…right here, and it says here that the coreml tools…are a Python package for creating, examining…and testing models in the mlmodel format.…So, we can use other models and just convert them…and, in order for this to work…since this is using Python, we're going…to setup everything you need in order for that to work.…
So, let's open up the terminal and, first of all,…install or upgrade the pip-tools…
- What are machine learning, Core ML, Vision, and NLP?
- Adding a machine learning model to a project
- Getting predictions from machine learning models
- Converting existing machine learning models for Core ML
- Classifying images and detecting objects with Vision and Core ML
- Analyzing natural language text with NSLinguisticTagger