There are a few best applications of it which gave rise to some of the most awesome and amazing artificial intelligence apps. A lot of these applications include:
Google Translate application: Here Google translate uses its neural networks to translate one language into another language using Google's TensorFlow library . These translation qualities are very good as compared with other machine translation systems such as Microsoft Translator, Systran etc.
Though there were many doubts about its accuracy at first, but since then google has done a lot of improvements on their neural network so now it is much more accurate than before. In a short span of time, this application has far surpassed the expectations and is at the first spot in language translation apps
Google's machine learning group recently released its visual recognition technology as an open source project called TensorFlow Hub . This project lets you discover, download , and use different modules for image classification and object detection . It uses deep convolutional neural networks to detect and classify every object within an image. These library categorize the objects like dog, cat, person etc on its own by just passing one sample image through it without any prior training required .
The Most important task that we can do with these libraries is to translate images into videos. Google Brain team has done some amazing work using these libraries in which they have demonstrated :
Reconstruction of a video from 32 individual frames, each frame extracted using adversarial attacks against deep neural networks. A video can be reconstructed with less than 50% accuracy Instance Segmentation which detects the object of interest on an input image and it then generates a mask that describes where the instance is located within the image. This library can generate a mask for every instance in one picture based upon three different representation models . It outputs multiple masks for overlapping instances You can also find many other applications utilizing this library such as Automatic Speech Recognition , Image to Text etc .
This code enables you to easily convert hand written digit images into real-valued vector data suitable for use in machine learning. The pre-trained weights are provided by Google's Handwriting model and so no training is required for using this code. The goal of this project is to provide a deep learning based approach for recognizing digits from images . Though it has not been able to match the accuracy of commercial products yet, but since its open source , it may be used as an excellent resource for teaching and research.
While we are still impressed by the early apps of machine learning technology, it introduces us to deep learning. The primary software tool for deep learning is TensorFlow.
TensorFlow took the world by storm because it is free, easy to use and provides developers with entry-level ML backgrounds access to a powerful library.
To start with TensorFlow, a developer needs to know:
The main cases of using TensorFlow:
