Machine Learning, Python, Towards Data Science, Dimensionality Reduction, Data Visualization.
contains the data and self.dtype=tf.float32 def fit(self): self.graph = tf.Graph() with self.graph.as_default(): self.X = tf.placeholder(self.dtype, shape=self.data.shape) # Perform SVD singular_values, u, _ = tf.svd(self.X) # Create sigma matrix sigma = tf.diag(singular_values) with