Applied Deep Learning with Python

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English | (August 31, 2018) | ISBN: 1789804744 | 334 pages | EPUB | 33.94 MB

Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions



A hands-on guide to deep learning that’s filled with intuitive explanations and engaging practical examples



Key Features

Designed to iteratively develop the skills of Python users who don’t have a data science background

Covers the key foundational concepts you’ll need to know when building deep learning systems

Full of step-by-step exercises and activities to help build the skills that you need for the real-world

Book Description

Taking an approach that uses the latest developments in the Python ecosystem, you’ll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We’ll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It’s okay if these terms seem overwhelming; we’ll show you how to put them to work.



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