Deep Learning in Python Prerequisites: Master Data Science and Machine Learning with Linear Regression and Logistic Regression in Python (Machine Learning in Python) by LazyProgrammer

Author:LazyProgrammer [Unknown]
Language: eng
Format: epub, azw3, pdf
Published: 2016-03-18T23:00:00+00:00

With deep learning and neural networks, we typically use (0, 1).

Although the visualizations used in this section were necessarily in 2 dimensions, note that all the techniques used do not require knowing what the dimensionality of the input is.

In real-world problems, we come across data that is hundreds or even thousands of dimensions. A dataset like MNIST contains 28 x 28 images. That’s 784 features per sample. Those are very tiny images in only one color. Another dataset, the street view house number dataset, contains color images of house numbers that are 32 x 32. While still a very tiny image, the fact that we need to account for the 3 color dimensions (R, G, B) means that each input vector is 3 x 32 x 32 = 3072 dimensions!

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