Books > Computing & IT > Computer programming > Programming languages
|
Buy Now
Applied Deep Learning with Python - Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions (Paperback)
Loot Price: R1,302
Discovery Miles 13 020
|
|
Applied Deep Learning with Python - Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions (Paperback)
Expected to ship within 10 - 15 working days
|
Donate to Gift Of The Givers
Total price: R1,322
Discovery Miles: 13 220
|
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 DescriptionTaking 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.
We'll build upon our classification coverage by taking a quick look
at ethical web scraping and interactive visualizations to help you
professionally gather and present your analysis. It's after this
that we start building out our keystone deep learning application,
one that aims to predict the future price of Bitcoin based on
historical public data. By guiding you through a trained neural
network, we'll explore common deep learning network architectures
(convolutional, recurrent, generative adversarial) and branch out
into deep reinforcement learning before we dive into model
optimization and evaluation. We'll do all of this whilst working on
a production-ready web application that combines Tensorflow and
Keras to produce a meaningful user-friendly result, leaving you
with all the skills you need to tackle and develop your own
real-world deep learning projects confidently and effectively. What
you will learn Discover how you can assemble and clean your very
own datasets Develop a tailored machine learning classification
strategy Build, train and enhance your own models to solve unique
problems Work with production-ready frameworks like Tensorflow and
Keras Explain how neural networks operate in clear and simple terms
Understand how to deploy your predictions to the web Who this book
is forIf you're a Python programmer stepping into the world of data
science, this is the ideal way to get started.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.