GEOMETRIFYING TRIGONOMETRY TENSORFLOW FOR SHAPE MINING AND THEOREMS GENERATOR
GEOMETRIFYING TRIGONOMETRY TENSORFLOW FOR SHAPE MINING AND THEOREMS GENERATOR TensorFlow can be used to do shape mining from large numbers of 2D line segment data. Here are the steps involved: First, you need to load the 2D line segment data into TensorFlow. This can be done using the tf.data.Dataset API. Once the data is loaded, you need to define a shape mining algorithm. This algorithm will typically involve finding patterns in the line segment data that correspond to different shapes. You can then use TensorFlow to train a model to implement the shape mining algorithm. This can be done using the tf.keras API. Once the model is trained, you can use it to mine shapes from new data. Here is an example of a shape mining algorithm that can be implemented in TensorFlow: Python def shape_mining_algorithm(line_segments): """Mines shapes from a set of 2D line segments. Args: line_segments: A list of 2D line segments. Returns: A list of s...
