Machine Learning for OpenCV
Michael Beyeler
- 出版商: Packt Publishing
- 出版日期: 2017-07-14
- 定價: $1,650
- 售價: 6.0 折 $990
- 語言: 英文
- 頁數: 382
- 裝訂: Paperback
- ISBN: 1783980281
- ISBN-13: 9781783980284
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相關分類:
影像辨識 Image-recognition、Machine Learning
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相關翻譯:
機器學習:使用 OpenCV 和 Python 進行智能圖像處理 (Machine Learning for OpenCV) (簡中版)
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其他版本:
Machine Learning for OpenCV 4 : Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn, 2/e (Paperback)
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相關主題
商品描述
Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide.
About This Book
- Load, store, edit, and visualize data using OpenCV and Python
- Grasp the fundamental concepts of classification, regression, and clustering
- Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide
- Evaluate, compare, and choose the right algorithm for any task
Who This Book Is For
This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks.
What You Will Learn
- Explore and make effective use of OpenCV's machine learning module
- Learn deep learning for computer vision with Python
- Master linear regression and regularization techniques
- Classify objects such as flower species, handwritten digits, and pedestrians
- Explore the effective use of support vector machines, boosted decision trees, and random forests
- Get acquainted with neural networks and Deep Learning to address real-world problems
- Discover hidden structures in your data using k-means clustering
- Get to grips with data pre-processing and feature engineering
In Detail
Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine
商品描述(中文翻譯)
擴展您的OpenCV知識,並通過這本實用的實踐指南掌握機器學習的關鍵概念。
關於本書
- 使用OpenCV和Python加載、存儲、編輯和可視化數據
- 掌握分類、回歸和聚類的基本概念
- 通過這本易於理解的指南,了解、執行和實驗機器學習技術
- 評估、比較和選擇任務的合適算法
本書適合對OpenCV已有基礎的Python程序員,將為您提供構建實際世界任務定制的機器學習系統所需的工具和理解。
您將學到什麼
- 探索並有效利用OpenCV的機器學習模塊
- 使用Python學習計算機視覺的深度學習
- 掌握線性回歸和正則化技術
- 對象分類,如花卉物種、手寫數字和行人
- 探索支持向量機、提升決策樹和隨機森林的有效使用
- 熟悉神經網絡和深度學習,解決實際問題
- 使用k-means聚類發現數據中的隱藏結構
- 掌握數據預處理和特徵工程
詳細內容
機器學習不再只是一個流行詞,它無處不在:從保護您的電子郵件,到自動標記照片中的朋友,再到預測您喜歡的電影。計算機視覺是當今最令人興奮的機器應用領域之一。