Tensorflow Machine Learning

Summary

Are you interested in learning machine learning and deep learning? TensorFlow is the single most popular library available today. Offering some of the very best graph computations, TensorFlow helps data scientists in designing neural networks using a cool feature called TensorBoard. It has support for both recurrent neural networks (RNNs) and convolution, as well as parallel processing support on GPU and CPU.   While TensorFlow is an incredibly important machine and deep learning library, we also give you an introduction to three others - NumPy, Pandas, and Scikit Learn. I have produced a hands-on guide, with plenty of code examples for you to follow along with. Here’s what you will learn:  What deep learning is  The difference between deep learning and machine learning  What TensorFlow is  How to install it on Windows and Mac  The basics of TensorFlow  Using TensorBoard  About NumPy, Scikit Learn, and Pandas  About linear regression  Kernel methods  Building an artificial neural network using TensorFlow  TensorFlow image classification  TensorFlow autoencoders  Much more  If you are already proficient at programming in Python and are ready to take the next step into machine learning, this guide is for you. Scroll up, hit that "Buy Now" button, and set off on a brand-new machine learning journey. 

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