Google TensorFlow: Machine learning or Machine learning is a computing technology that has been evolving in recent years. This technology is used everywhere around us, from driving cars to predicting the stock market.
TensorFlow is a Google program based on machine learning and neural networks. Below we will look at exactly what can be used and how to learn to use it.
What is TensorFlow?
To explain what TensorFlow is, we must first understand what mechanical learning is. Mechanical learning and neural networks already affect our lives in much more ways than you think.
Machine learning could be said to be the process of teaching computers to learn how to analyze data and how to make informed decisions, without being directly programmed for it.
In order to do this, we train neural networks that can perform specific tasks.
TensorFlow is a Google open source neural network library developed by the Google Brain team for many uses. Essentially, TensorFlow eliminates the need to create a neural network from the start. So, once the base is in place, you can train TensorFlow with your own data and use the results you want.
Does it seem abstract to you? What can you do with a neural network? Let's look at some examples of TensorFlow
Sorting pictures
Many training seminars for novice users use image sorting to help understand. By providing reference pictures on a neural network, the network can learn (mechanically) whether an image contains similar objects.
To see this process in action, take a look at Darth Vader classifier by Siraj Raval.
This kind of assisted sorting of data from the computer is incredibly powerful and not just the way it is used in the video. TensorFlow is already used in biomedical image analysis.
Almost every field based on the analysis of large amounts of image data can benefit from this technology. As shown in the official TensorFlow presentation video, it's used in medicine, art, Gmail, or wherever you can imagine.
Deep Photo Style Transfer
In addition to image sorting, TensorFlow can be used to dynamically change images. Deep Photo Style was developed by a team at University of Cornell. The project takes two different photos and creates a new style image from both original, with amazing results.
Magenta AI Music
What can you say about creating artworks? With nerve network libraries like TensorFlow, it can become reality.
Magenta uses TensorFlow to create tools for musicians. Using deep learning, Magenta creates the right tools that musicians need for new sound mixing, and much more.
By creating improvised musical pieces created by the nervous network, the Magenta allows anyone to create unique and beautiful sounds without having any musical knowledge.
How to Learn TensorFlow
Machine learning is not easy. We need a good understanding of statistics, math, 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 tutorials TensorFlow guides you step by step for every setting and every use.
Most TensorFlow projects use the Python programming language. If you do not know it, there are many websites that help you learn Python (Dive Into Python, Official Python Tutorial, TryPython ή LearnPython). If you already know JavaScript, TensorFlow has video tutorials for the TensorFlow.js library.
These lessons, along with Google's free mechanical learning, will help you understand every project.
TensorFlow is an incredibly powerful tool from the largest internet company. The decision to make it available as an open source makes technology accessible to everyone (those who are willing to learn).
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