Google TensorFlow: Machine learning is a computing technology that has been evolving continuously in recent years. This technology is used everywhere around us, from driving cars to predicting the stock market.
TensorFlow is a Google program that is based on machine learning and neural networks. Below we will see what it is exactly, where it can be used and how to learn to use it.
What is TensorFlow?
To explain what TensorFlow is, we first need to understand what machine learning is. Machine learning and neural networks are already affecting our lives in more ways than you might think.
Machine learning is the process of teaching computers to learn how to analyze data and make informed decisions without being programmed to do so.
To do this, we train neural networks that can perform specific tasks.
TensorFlow is an open-source neural network library from Google, developed by the Google Brain team for a wide range of uses. Essentially, TensorFlow eliminates the need to build a neural network from scratch. So since the foundation is already there, you can train TensorFlow with your own data and use the results you want.
Sounds abstract? What can you do with a neural network? Let's look at some examples of TensorFlow
Sorting images
Many beginner tutorials use image classification to help with understanding. By feeding a neural network reference images, the network can learn (mechanically) to predict whether an image contains similar objects.
To see this process in action, take a look at Siraj Raval's Darth Vader classifier.
This kind of computer-assisted data sorting is incredibly powerful, and not just in the way it’s used in video. TensorFlow is already being used in image analysis from biomedical to computer science.
Almost any field that relies on analyzing large amounts of image data can benefit from this technology. As you can see in the official TensorFlow presentation video, it’s being used in medicine, art, Gmail, and pretty much anywhere else you can imagine.
Deep Photo Style Transfer
In addition to image classification, TensorFlow can be used to dynamically alter images. Deep Photo Style Transfer was developed by a team at Cornell University. The project takes two different photos and creates a new image with styles from both originals, with stunning results.
Magenta AI Music
What can you say about creating artwork? With neural network libraries like TensorFlow, it can become a reality.
Magenta uses TensorFlow to build tools for musicians. Using deep learning, Magenta creates the right tools musicians need to create new types of sound mixing, and much more.
By creating improvised musical pieces generated by the neural network, Magenta allows anyone to create unique and beautiful sounds without having any musical knowledge.
How to learn TensorFlow
Machine learning is not easy. It requires a good understanding of statistics, mathematics, programming, and general data science, as all of the above are necessary to teach a machine to “think” and make decisions. But TensorFlow offers lessons even for beginners. The official TensorFlow tutorials guide you step by step through each setup and use.
Most TensorFlow projects use the Python programming language. If you don’t know it, there are many websites that help you learn Python (Dive Into Python, Official Python Tutorial, TryPython or LearnPython). If you already know JavaScript, TensorFlow has video-tutorials for the TensorFlow.js library.
These courses, along with Google's free machine learning, will help you fully understand any project.
TensorFlow is an incredibly powerful tool from the largest company on the Internet. The decision to make it open source makes the technology accessible to everyone (those who are willing to learn).
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