Compare the Top Machine Learning Apps for iPhone as of May 2025

This a list of Machine Learning apps for iPhone. Use the filters on the left to add additional filters for products that have integrations with iPhone. View the products that work with iPhone in the table below.

What are Machine Learning Apps for iPhone?

Machine learning software enables developers and data scientists to build, train, and deploy models that can learn from data and make predictions or decisions without being explicitly programmed. These tools provide frameworks and algorithms for tasks such as classification, regression, clustering, and natural language processing. They often come with features like data preprocessing, model evaluation, and hyperparameter tuning, which help optimize the performance of machine learning models. With the ability to analyze large datasets and uncover patterns, machine learning software is widely used in industries like healthcare, finance, marketing, and autonomous systems. Overall, this software empowers organizations to leverage data for smarter decision-making and automation. Compare and read user reviews of the best Machine Learning apps for iPhone currently available using the table below. This list is updated regularly.

  • 1
    RunLve

    RunLve

    RunLve

    Runlve sits at the center of the AI revolution. We provide data science tools, MLOps, and data & model management to empower our customers and community with AI capabilities to propel their projects forward.
    Starting Price: $30
  • 2
    OpenCV

    OpenCV

    OpenCV

    OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.
    Starting Price: Free
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