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RELEASE NAME....: Pluralsight.com.Predictive.Analytics.with.PyTorch-ELOHiM
RELEASE DATE....: 2020-05-10
RELEASE SIZE....: 19x15Mb
FORMAT..........: Bookware
LANGUAGE........: English
URL.............: https://www.pluralsight.com/courses/predictive-analytics-pytorch
PyTorch is fast emerging as a popular choice for building deep
learning models owing to its flexibility, ease-of-use and
built-in support for optimized hardware such as GPUs. In this
course, Predictive Analytics with PyTorch, you will see how to
build predictive models for different use-cases, based on the
data you have available at your disposal, and the specific nature
of the prediction you are seeking to make.
First, you will start by learning how to build a linear
regression model using sequential layers. Next, you will explore
how to leverage recurrent neural networks (RNNs) to capture
sequential relationships within text data. Then, you will apply
such an RNN to the problem of generating names - a typical
example of the kind of predictive model where deep learning far
out-performs traditional natural language processing techniques.
Finally, you will see how a recommendation system can be
implemented in several different ways - relying on techniques
such as content-based filtering, collaborative filtering, as well
as hybrid methods.
When you are finished with this course, you will have the skills
to build, evaluate, and use a wide array of predictive models in
PyTorch, ranging from regression, through classification, and
finally extending to recommendation systems.
Level: Intermediate
Released: May 01, 2020
Duration: 2h 31m