TensorFlow is an end-to-end platform for machine learning. We have already discussed what machine learning is.
In addition, we have also seen the difference between machine learning and artificial intelligence.
Here we’ll learn TensorFlow, created by Google Brain Team. TensorFlow is a Software library for Machine Learning, and Artificial Intelligence.
It uses Python, so we’ll learn it.
However, to master Machine Learning we need to learn a section of Mathematics also.
For the sake of library support we’ll mostly code in Google Colab.
Firstly, let’s see what TensorFlow supports.
Secondly, our primary goal is to make things as simple as possible.
Why?
Because a beginner can learn machine learning through TensorFlow.
Finally we will try to move forward from lesser known facts to unknown facts.
However, we will try to make it simple.
First thing first.
We have seen multi dimensional computation before. Right?
Because NumPy does the same thing.
TensorFlow supports the same thing.
Therefore, if you know python list, NumPy arrays, you will pick up TensorFlow quickly.
If not, please check the NumPy category where we have tons of articles.
TensorFlow also supports Graphic processing units, or GPU and distributed processing.
We’ll learn them as we progress.
TensorFlow supports Automatic differentiation, or AD in machine learning. It’s an advanced technique. As a result, as a beginner, you need some time to reach that stage.
But we’ll discuss them as well.
Finally as we learn machine learning we will see how to make Model construction, training, and export them.
Certainly our learning curve is a little bit steep. Unfortunately there is no quick process to learn TensorFlow. But if you stick to it, you will definitely learn them.
Just be patient and stay tuned.
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