You're reading from Modern Computer Vision with PyTorch

Product typeBook

Published inNov 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781839213472

Edition1st Edition

Languages

Python

Tools

PyTorch

Concepts

Computer Vision

Authors (2):

V Kishore Ayyadevara

Yeshwanth Reddy

View More author details

Questions

What are the various layers in a neural network?
What is the output of feedforward propagation?
How is the loss function of a continuous dependent variable different from that of a binary dependent variable and also of a categorical dependent variable?
What is stochastic gradient descent?
What does a backpropagation exercise do?
How does a weight update of all the weights across layers happen during backpropagation?
Which functions of a neural network happen within each epoch of training a neural network?
Why is training a network on a GPU faster when compared to training it on a CPU?
How does the learning rate impact training a neural network?
What is the typical value of the learning rate parameter?

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Modern Computer Vision with PyTorch

Published in: Nov 2020Publisher: PacktISBN-13: 9781839213472

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Authors (2)

V Kishore Ayyadevara

V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara

Yeshwanth Reddy

Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more about Yeshwanth Reddy

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