Predicting using TensorFlow Machine Learning Libray is said to be easy to implement. For example,
(1). Make sure that python > 2.7 is installed
(2). Make sure that you are able to install Python libraries using pip or pandas (Another Complicated Thing To Do (Read More)). These platforms are like using npm when developing in JavaScript/Typescript/Angular/NodeJS.
After you verify that python is installed and that you are able to install python libraries, read through TensorFlow Getting Started Documentation and see how you can install TensorFlow on the computer/local machine/virtual environment and how to activate it.
[NB] It is easy to follow TensorFlow documentation about Estimators (Read about preexisting Estimator to see how the library predicts). Take note that, there are different estimators, if one estimator doesn't work for you, experiment with another until you see a high confidence level (Probability/chances of happening) of 0.95 or 0.98 of the prediction.
After all the above is completed, clone one of the examples and start playing with. One thing I have discovered is that it is kind of hard to prepare your data (defined in Column for the module to train on) to comply with an Estimator. Research about it and you will find out more information.
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