£71.46

Practical Deep Learning for Computer Vision with Python

AI & Machine Learning

Price data last checked 104 day(s) ago - refreshing...

View at Amazon

We'll watch every seller, every day. One email when your price arrives.

It has never been this cheap. We have no record of a lower price.

£71 today · cheaper than every other day in the last 24 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 627 days • 627 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 627 days • 1 price levels

Days at Price

Price Analysis

Most common price: £71 (627 days, 100.0%)

Price range: £71 - £71

Price levels: 1 different prices over 627 days

Description

DeepDream, Keypoint Detection, Image Captioning with KerasNLP Transformers and ConvNets, Semantic Segmentation with DeepLabV3+, Real-Time Object Detection from Videos with YOLOv5, Large-Scale Breast Cancer Classification... and more. Computer Vision is an exciting and almost prohibitively large field - and it's experiencing the largest advancements it has ever seen, in the past few years. We won't be doing classification of MNIST digits or MNIST fashion. They served their part a long time ago. Too many learning resources are focusing on basic datasets and basic architectures before letting advanced black-box architectures shoulder the burden of performance. We want to focus on demystification, practicality, understanding, intuition and real projects. Want to learn how you can make a difference? We'll take you on a ride from the way our brains process images to writing a research-grade deep learning classifier for breast cancer to reading and implementing papers, to deep learning networks that "hallucinate", teaching you the principles and theory through practical work, equipping you with the know-how and tools to become an expert at applying deep learning to solve computer vision. There's a plethora of tools, libraries and concepts used to make work easier and its results more robust. Also, these tools don't always work, especially when you want to combine them - you should know why you're applying a tool or library and when they can make a difference. We want this book to not only teach you the technical side of Computer Vision, but also how to be a Computer Vision engineer. It's meant for the researcher looking to apply computer vision to their field (medical imagery, agriculture, manufacturing, urbanism, etc.), the student who's looking to break into new roles, the software engineer to empower their code and for the data enthusiast. This book was written for anyone with a basic understanding of machine learning and deep learning looking to orient themselves towards, or initially step into, computer vision. The book primarily uses Keras - the official high-level API for TensorFlow, with some PyTorch in later lessons. While prerequisite knowledge of Keras isn't strictly required, it will undoubtedly help. I won't be explaining what an activation function is, how cross-entropy works, or what weights and biases are. There are amazing resources covering these topics, ranging from free blogs to paid books - and covering these topics would inherently steer the focus of the book in a different direction than it's intended to be set in. The book is written to be advanced but beginner-friendly, with layers to be extracted through multiple reads. Contents Preface Introduction to Computer Vision Guide to Convolutional Neural Networks Guided Project: Building Your First Convolutional Neural Network With Keras Overfitting Is Your Friend, Not Your Foe Image Classification with Transfer Learning ‑ Creating Cutting Edge CNN Models Guided Project ‑ Breast Cancer Classification with Keras Convolutional Neural Networks ‑ Beyond Basic Architectures Working with KerasCV Object Detection and Segmentation ‑ R‑CNNs, RetinaNet, SSD, YOLO... Guided Project: Real‑Time Road Sign Detection with YOLOv5 Guided Project: Image Captioning with CNNs and Transformers Guided Project: DeepLabV3+ Semantic Segmentation with Keras DeepDream ‑ Neural Networks That Hallucinate? Optimizing Deep Learning Models for Computer Vision

Product Specifications

Format: Paperback
ASIN: B0BF2Q747G
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 15 September 2022
Listed Since: 16 September 2022

Barcode

No barcode data available

Practical Deep Learning for Computer Vision with Python

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Modern Computer Vision with PyTorch: A practical roadmap from deep learning fundamentals to advanced applications and Generative AI

Computer Vision Projects with PyTorch: Design and Develop Production-Grade Models

Computer Vision: Algorithms and Applications (Texts in Computer Science)

An Introduction to Image Classification: From Designed Models to End-to-End Learning

Computer Vision: Algorithms and Applications (Texts in Computer Science)

Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications

Advances in Computer Vision: Proceedings of the 2019 Computer Vision Conference (CVC), Volume 1: 943 (Advances in Intelligent Systems and Computing, 943)

A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision)

Computer Vision: Models, Learning, and Inference

Deep Learning Models: A Practical Approach for Hands-On Professionals (Transactions on Computer Systems and Networks)

Computer Vision: Principles, Algorithms, Applications, Learning

Practical Machine Learning for Computer Vision: End-to-End Machine Learning for Images

Computer Vision: Object Detection In Adversarial Vision - CRC

Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection: 124 (Intelligent Systems Reference Library, 124)

Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy

Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection: 124 (Intelligent Systems Reference Library, 124)

Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition)

Topics in Medical Image Processing and Computational Vision: 8 (Lecture Notes in Computational Vision and Biomechanics, 8)

Computer Vision Methods for Fast Image Classiﬁcation and Retrieval: 821 (Studies in Computational Intelligence, 821)

Computer Vision: Three-dimensional Reconstruction Techniques

Foundations of Computer Vision (Adaptive Computation and Machine Learning)

Digital Image Processing and Analysis: Computer Vision and Image Analysis

Computer Vision - ACCV 2006: 7th Asian Conference on Computer Vision, Hyderabad, India, January 13-16, 2006, Proceedings, Part I: 3851 (Lecture Notes in Computer Science, 3851)

Computer Vision – ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part I: 9913 (Lecture Notes in Computer Science, 9913)