New Directions in Deep Learning

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  • GANs in Action
  • Data Science with Python and Dask
  • Practical Recommender Systems
$119.97$59.99 New Directions in Deep Learning Bundles are not eligible for additional discounts.

GANs in Action

GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you’ll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you’ll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks.

As you work through the book’s captivating examples and detailed illustrations, you’ll learn to train different GAN architectures for different scenarios. You’ll explore generating high-resolution images, image-to-image translation, and adversarial learning, as well as targeted data generation, as you grow your system to be smart, effective, and fast.

Data Science with Python and Dask

Data Science with Python and Dask teaches you how to build distributed data projects that can handle huge amounts of data. You’ll begin with an introduction to the Dask framework, concentrating on how Dask natively scales commonly-used Python libraries like Numpy and Pandas. With a particular focus on data analysis, you’ll immediately start exploring the huge amount of data found in the NYC 2013-2017 Parking Ticket database. You’ll be introduced to Dask DataFrames and learn helpful code patterns to streamline your analysis. You’ll also dig into visualization with Seaborn and learn to build machine learning models using Dask-ML.

As you work through Dask’s features, you’ll learn how to prepare and analyze the dataset to discover trends and patterns in NYC’s parking enforcement operations. How does the time of year and weather affect issued citations? Is the number of citations rising or falling? You’ll find out, and you’ll figure out how to discover similar trends in your own data! Along the way, you’ll look deeper into Dask Arrays and Bags, use Datashader to build interactive location-based visualizations, and learn to implement your own algorithms using custom task graphs. Finally, you’ll learn how to scale your Dask apps and learn how to build your very own Dask cluster using AWS and Docker.

Practical Recommender Systems

Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you’ll see how to collect user data and produce personalized recommendations. You’ll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you’ll encounter as your site grows.

$119.97$59.99 New Directions in Deep Learning Bundles are not eligible for additional discounts.
Some bundled books and liveVideos are part of the Manning Early Access Program. You'll get all the available content now, new content as it's created, and the final product when it's ready.