Description

Machine learning is hard. But it doesn't have to be. Between the linear algebra, multivariate calculus, probability theory, topology, and statistics, machine learning can seem all but impossible without a PhD in mathematics. The reality is that you can understand and become proficient in machine learning with the math skills of an eighth grader.

In Henry Dang's, The Mostly Mathless Guide to TensorFlow Machine Learning, you will learn the high-level ideas behind machine learning, and even create several different kinds of neural networks, all without knowing any of the complicated math. At its core, machine learning is simple and beautiful. But this simplicity can be lost in the large waves of long formulas and complicated math symbols.

In this book, you will be able to

• Understand the key ideas behind machine learning and neural networks, without any of the math


• Understand the why behind machine learning, and not just the how


• Use Python and TensorFlow to create machine learning programs


• Create three different kinds of neural networks -- vanilla neural networks, convolutional neural networks, and recurrent neural networks


• Accurately identify handwritten numbers with up to a 99% accuracy using the MNIST dataset, in multiple different ways