Machine learning is becoming more and more popular in almost every aspect of our world.
From providing interesting and stimulating games to creating recognition technology to improve safety, it is becoming more important than ever to learn about machine learning programs.
One such program is TensorFlow. In this article, we will look at what you can build using TensorFlow and provide you with some amazing ideas to get you started.
What Is TensorFlow?
TensorFlow is an end-to-end open source platform that is used for machine learning. The platform has been designed so that it can be used by both beginners and experienced users to create machine learning models.
TensorFlow has a particular focus on deep learning which is a subset of machine learning in which large-scale unstructured data is analyzed.
Why Use TensorFlow?
TensorFlow was created by the Google Brain Team for internal use. However, in November 2015, it was released to the public.
The platform was given a huge update in 2021 which provided library improvements, better GPU performance, and an automatic differentiation scheme among other features.
One of the best things about TensorFlow is that it isn’t just restricted to deep learning. Through the platform, you can also utilize deep neural networks to make the processing of data easier. A lot of the features that are possible with TensorFlow are due to the fact that it is written using multiple languages including C++, Python, and CUDA.
What Can You Build With TensorFlow?
When you are using TensorFlow, there are several projects that you can undertake. With that being said, there are three main applications for TensorFlow that are most commonly used. These include:
Large-scale linear models: used for data analysis and basic behavioral predictions
Convolutional neural networks (CNN): used for image recognition and processing
Sequence-2-sequence (seq2seq): models that allow human language-related features
Almost all projects that are created with TensorFlow stem from one of these three applications in some form. Because the platform is so user-friendly, users can create almost anything provided that they have an active and curious imagination.
Popular Projects Ideas For TensorFlow
Now that you know what TensorFlow can be used for and that it is suitable for beginners as well as experienced users, it is time to look at some of the best projects that you create using the platform.
Below are some of the most interesting things that you can do with TensorFlow.
Machine learning platforms such as TensorFlow can be used to help solve problems such as mathematical games. Sudoku is one of those games.
A TensorFlow project that aims to create sudoku needs to make a solver bot that is capable of analyzing a sudoku grid and filling it appropriately by utilizing simple mathematical rules.
The autonomous robot requires hardware including a Raspberry Pi and a camera to allow it to take a photo of the grid. The TensorFlow imaging processing function and recognition network allow it to work towards a numerical representation of the grid.
It is also possible to build vehicle detection systems using TensorFlow. For this project, you will need to use the TensorFlow object counting API function.
This is used for detecting, tracking, and counting objects or vehicles in this case. To make this project a bit of a challenge, you may also need to use classification features.
This project requires TensorFlow and OpenCV which is a library of programming functions for computer vision.
These two features work together in vehicle detection. OpenCV deals with color prediction, pixel manipulation, and calculation programs to predict speed, TensorFlow uses object detection API and SSD to fully process the final frame output.
If you are looking for a project that is perfect for beginners, deep speech is a great option. This project uses TensorFlow libraries to create a text-to-speech converter. This is a great way to learn the ability of the TensorFlow framework to process language.
To make this project a little more complex, you can implement hardware such as a Raspberry Pi, Arduino, and High-powered GPU servers.
Using the ImageNet classifier on the TensorFlow platform, it is possible to identify thousands of objects. This allows the project to identify particular obstacles correctly. This is a really fun and simple project that is perfect for beginners.
Users can set up simple retraining scripts that train their models to identify additional objects.
If you are familiar with machine learning technology and want a more challenging project, it is possible to make a pair of smart glasses that can help blind people be aware of what is going on in their immediate surroundings.
This project uses a Raspberry Pi3 and Google Android Things. TensorFlow provides the power.
In addition to the hardware mentioned above, you will also need a camera and button to make this project work.
The idea is that when the button on the device is pressed by a visually impaired person, the glasses capture an image of the surroundings and a voice assistant guides the individual past detected obstacles.
Music Genre Classification
This is a fun project that is perfect for people who are experienced with machine learning platforms and want to experiment with TensorFlow. This project is designed to automatically identify different genres of music using different sounds and tones.
TensorFlow identifies and analyzes different sounds. Audio files are classified by the platform by their low-level frequency and time domain. They are then arranged using multi-level binary classification for better precision.
Another project suitable for advanced-level users is sentiment analysis. This project is designed to analyze the emotions of users. The project uses the facial recognition function in TensorFlow as well as the ImageNet classifier and a camera.
The project captures the user’s image and then categorizes the emotions of the face as negative, neutral, or positive. This project requires a significant amount of deep learning for the program to successfully categorize emotions with high accuracy.
A good beginner project with TensorFlow is detecting spam. This project is very similar to the system that is used by Gmail to block over 99.9% of phishing emails and malicious software from ever reaching your inbox.
Building a basic spam detection model with TensorFlow is super simple and great for getting to know the platform.
You will need to create a recurrent bureau network trained with a data set similar to the Spam Text Message Classification. The basic spam detection model will not produce the same performance as Google but the premise is the same.
TensorFlow is a great machine learning platform that can be used by beginners and experts to create a variety of projects. There are plenty of projects that you can complete with very little additional software.
The multiple languages used in the platform also help to broaden your knowledge in the field.
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