In machine learning, a TensorFlow model state machine is a function with learnable parameters that maps an input to an output. The optimal parameters are obtained by training the model on data. A well-trained TensorFlow model will provide an accurate mapping from the input to the desired output. As the flowchart diagram below illustrates, TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications. After the process starts, you will be asked to import the data, and after studying the dataset, you can apply the pre-processing techniques to build a TensorFlow Model.