Even the most casual followers of technology have realized by now that AI is rapidly expanding to all domains of technology, and mobile applications are perhaps the first ones to be invaded.
The latest trend is that regardless of the coolest and most elaborate features, your app is irrelevant if it doesn’t learn from user behavior and offers custom solutions. .
From Google to Apple to Microsoft, every tech titan in their keynote this year have r hinted that this shift from applications to smart applications is prominent and developers should definitely get started. To help them in the process, they have offered some very sophisticated frameworks that mobile app development services are scrambling to learn and master to ensure their stake in the future- Machine Learning enabled apps. There are the best ones on the market:
#1. Tensorflow
If you have used popular Google Services like Translate, Photos, Search, you have already experienced the power of Tensorflow as most of them use it at the backend. Initially developed by Google for research purposes in Machine Learning and Deep Neural Networks, this open-source library is one of the most advanced and mature frameworks you will find for the job.
The framework uses computational graph model and can be used to create solutions of all scales and complexities and is often a part of mobile app development environment for creating intelligent apps. Twitter, Snapchat, Uber, among many others, are just a few top-class applications that exploit the power of Tensorflow. Additionally, available for all platforms- Android, iOS, Windows, Mac, and Linux, it is also one of the most widely accessible.
#2. Core ML
Launched in 2017, Core ML is Apple’s framework for creating intelligent iOS apps. It supports a variety of Machine Learning models like Squeezenet, MobileNet, among others and gives developers the liberty to convert any other existing models into Core ML.
If you have used Apple’s products like Siri or QuickType, you already have a taste of what this framework can deliver. Developers can use this framework to make use of highly sophisticated computer vision, face recognition, text recognition, object tracking, and much more. The only issue here is that it is available only for iOS platform and that too for the version 11.0 and above.
#3. Cognitive Toolkit
Cognitive Toolkit is Microsoft’s take on creating ML-enabled applications and is available only for Windows and Linux platforms. Most of the products of Microsoft like Cortana, Skype, Bing, Xbox have been built using Cognitive Toolkit and reflect the wide range of features and capabilities that it can deliver.
Developers can use and create a wide range of models in C++, Python, and BrainScript to deploy Deep Learning capabilities in various environments including both hardware and application level.
#4. Amazon Machine Learning
Though the company has been considered a pioneer of AI and ML for a very long time, it is only after its Alexa and Cloud services that it truly has a stake in the developer community. It now offers a handy tool for creating intelligent apps without much looking under the hood.
The framework enables developers to use only visualization tools to create different models which are then implemented with APIs on the fly without them ever needing to write those complicated algorithms. Available for both Android and iOS, it is one of the best tools to use if you need to create an ML-enabled app in minimum time and limited budget with basic skills.
#5. Caffe Deep Learning Framework
Available for Windows, Linux and Mac platforms, it is one of the widely used frameworks for Convolutional Neural Networks to create machine vision, recommendation engine, among other applications. The model Zoo it uses is pre-trained to perform different tasks, thereby cutting short the time and efforts that mobile app developers would need to invest.
The only issue here is that it can’t be used for non-vision applications like audio, text or time series, which drastically limits its usability.
