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 •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.
Educated at Newberry College, Benjamin Smith is a veteran of newspapers and radio. Having reported the news and run radio stations covering breaking stories gave him a number of ideas for novels. Now in his middle years he has started striking pen to paper. He lives in Beaufort South Carolina with his wife Kim and their two children.