Machine learning is becoming popular from the last few of years. Nowadays every single software/app comes with machine learning implementation. There are so many languages and libraries for machine learning, but It needs a heavy powerful machine to train models.
Training neural networks require more power consumption and processing. Where mobile has a limited amount of battery and processing power. So, what if you want to do machine learning on mobile?
The answer is Tensorflow lite, It enables us to deploy a trained model into mobile. Tensorflow contains a converter, Interpreter core, operation kernels, and hardware acceleration delegations.
Tensorflow is also cross-platform that means you can do on android and ios anywhere you want.
How to use Tensorflow lite?
1. Get a model or Train model
2. Convert the model to Tensorflow lite
3. Write ops (if needed)
4. Write App
First, you need a model to implement in your app. So, you have to download the pre-trained model or you can train manually on your machine. There are lots of models are available like inception v3, Mobilenet.
After you get a model then you have to convert into Tensorflow lite format. Tensorflow is compatible with a lot of languages so you can train model into any language you want. After that just convert your model into Tensorflow lite format.
If you want to use Pre-trained model then it is ok but if you want to change something then you can. you can write your ops if you needed. By using neural networks API we can enable hardware acceleration.
After that, we have to write our APP. But before you write something, You need a dependency on it. You need to add a dependency in your Gradle file.
Also, you need to import your converted tensorflow lite model. you have to write code into try-catch block because it can cause an exception.
After doing all the things you are ready to implement machine learning to your App. The Tensorflow team is working on creating more models which you can use in your App development but still, there are lots of models available you can use right now. If you have enough powerful machine then you can train your own model as you want and you can implement it anywhere you like.
If you are struggling with learning AI then you can check this article on How to learn machine learning faster and better?
If you want full guidance on how to get started with AI then check our article How to get started with AI?
If you have any doubts related to this article you can feel free to ask in a comment or social media. Stay tuned for more Android, Machine learning articles, We will back soon with more interesting stuff.
After that, we have to write our APP. But before you write something, You need a dependency on it. You need to add a dependency in your Gradle file.
Also, you need to import your converted tensorflow lite model. you have to write code into try-catch block because it can cause an exception.
After doing all the things you are ready to implement machine learning to your App. The Tensorflow team is working on creating more models which you can use in your App development but still, there are lots of models available you can use right now. If you have enough powerful machine then you can train your own model as you want and you can implement it anywhere you like.
If you are struggling with learning AI then you can check this article on How to learn machine learning faster and better?
If you want full guidance on how to get started with AI then check our article How to get started with AI?
If you have any doubts related to this article you can feel free to ask in a comment or social media. Stay tuned for more Android, Machine learning articles, We will back soon with more interesting stuff.
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