Top Vision books recommended by experts

At MentorCruise, we are all about making the most out of the experience of others. As part of that, we've connected and asked dozens of experts and professionals about their favourite Vision books – and here are the answers.

Table of Contents

Fundamentals of Vision

Understanding the concepts of Vision starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.

Deep learning

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts …

Recommended by the experts and mentors at MentorCruise

Modern Computer Vision with PyTorch: Explore Deep Learning Concepts and Implement Over 50 Real-world Image Applications

Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions â–¶Book Description Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. ...

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Learning TensorFlow

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. It was developed by the Google Brain team for Google's internal use in research and production.

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Machine Learning Design Patterns

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. ...

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Computer Vision Metrics: Survey, Taxonomy, and Analysis

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. ...

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Deep Learning for Vision Systems

How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. ...

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Additional Vision Reading

These books are not required for you to learn Vision, but they are highly recommended for you to deepen your knowledge.

Practical Machine Learning for Computer Vision

This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. ...

Recommended by the experts and mentors at MentorCruise

Digital image processing

Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.

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Learning OpenCV 4 Computer Vision with Python 3: Get to Grips with Tools, Techniques, and Algorithms for Computer Vision and Machine Learning

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 4 and Python 3. ...

Recommended by the experts and mentors at MentorCruise

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  • "Naz is an amazing person and a wonderful mentor. She is supportive and knowledgeable with extensive practical experience. Having been a manager at Netflix, she also knows a ton about working with teams at scale. Highly recommended."

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