For those of us with an iPad and an interest in ML

In summary, Tinkerstellar is a free app that teaches python 3 and its popular modules. It also has a run code feature. The second app, Juno, costs $14.99 and offers the Juno IDE notebook interface for python as well as the ability to install third party modules. Pythonista, another app mentioned, is available in versions 2.7 and 3.6 with preloaded modules such as numpy and matplotlib.
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There are a couple of recent apps for iPad that can get you started in python 3 programming and ML applications.
The first is Tinkerstellar ($free), an app designed to teach you python 3 and some of its most popular modules including its ML modules (7 part tutorial) like Scikit-Learn and Pandas. It has a run code feature to show how python will execute example code.

The second app by the same developer is called Juno ($14.99) and it brings the Juno IDE notebook interface for python. Additionally, you can install third party python modules. My first impressions are this app is better in some cases than the more popular Pythonista app although Pythonista can do some cool interactive graphics apps And games with their Scene module.

You can find them both on the Apple AppStore.
 
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FAQ: For those of us with an iPad and an interest in ML

What is ML and how does it relate to the iPad?

ML, or machine learning, is a subset of artificial intelligence that involves training computers to learn and make decisions based on data without explicit programming. The iPad has the capability to run ML algorithms and applications, making it a valuable tool for those interested in the field.

What are some popular ML apps available for the iPad?

Some popular ML apps for the iPad include TensorFlow, Core ML, and IBM Watson Studio. These apps provide users with tools and resources for building and implementing ML models on their iPad.

Can I use my iPad to train ML models?

Yes, you can use your iPad to train ML models. However, the complexity and size of the models you can train may be limited by the processing power and storage capabilities of the iPad.

Are there any limitations to using ML on an iPad?

One limitation of using ML on an iPad is the smaller screen size compared to a computer, which may make it more difficult to visualize and analyze data. Additionally, the processing power and storage space on an iPad may be limited, making it more suitable for smaller or simpler ML tasks.

Can I integrate ML into my existing iPad apps?

Yes, you can integrate ML into your existing iPad apps through the use of ML frameworks and APIs, such as Core ML or TensorFlow Lite. These tools allow developers to incorporate ML capabilities into their apps, making it possible to create more intelligent and personalized experiences for users.

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