Thanks to TensorFlow Mobile and TensorFlow Lite, embedding and using deep models inside Android applications has become very easy. However, designing and training the models still requires a lot of skill, time, and effort, not to mention computing power. For this reason, most casual developers are unenthusiastic about adding machine learning-related capabilities to their apps. With Firebase ML Kit, Google hopes to change that.

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With TensorFlow, one of the most popular machine learning frameworks available today, you can easily create and train deep models—also commonly referred to as deep feed-forward neural networks—that can solve a variety of complex problems, such as image classification, object detection, and natural language comprehension. TensorFlow Mobile is a library designed to help you leverage those models in your mobile apps.

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The rise of artificial intelligence is triggering a paradigm shift in the field of user interface development. Thanks to the proliferation of intelligent, voice-activated assistants such as Google Home, Siri, and Alexa, users are beginning to feel that pressing numerous buttons on a screen or manually filling out forms is not only inefficient and slow, but also old-fashioned.

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A good approach to becoming proficient in a new programming language or library is to try and create something useful with it. In my tutorial on simplifying Android development with Anko, I introduced you to Anko’s domain-specific language and helper functions. Although I’m sure you found them impressive, you might still be apprehensive about using them in large and complex apps, since they are so different from traditional Android classes and methods.

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