Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies. In this beginner-friendly course you will understand about computer vision, and will learn about its various applications across many industries. As part of this course you will utilize Python, Watson AI, and OpenCV to process images and interact with image classification models. You will also build, train, and test your own custom image classifiers. This is a hands-on course and involves several labs and exercises. All the labs will be performed on the Cloud and you will be provided access to a Cloud environment completely free of charge. At the end of the course, you will create your own computer vision web app and deploy it to the Cloud. This course does not require any prior Machine Learning or Computer Vision experience, however some knowledge of Python programming language is necessary.
Этот курс входит в специализацию ''Профессиональная сертификация 'IBM Applied AI''
Introduction to Computer Vision with Watson and OpenCV
от партнера
- Machine Learning Engineers
- Data Scientists
- Technical Solutions Engineers
- Founders
- Software Engineers
Приобретаемые навыки
Программа курса: что вы изучите
Introduction to Computer Vision
This short module will introduce you to the field of computer vision. We will cover the course expectations and highlight how computer vision is making an impact across various industries. You will also be introduced to the tools used in computer vision.
Image Classification with IBM Watson
In this module, we start by introducing the topic of image classification. We will then talk about Watson Visual Recognition, an industry-leading service provided by IBM that is used for image classification. Finally, you will create your own instance of Watson Visual Recognition and will use it to upload images and perform image classification. Let's get started!
Custom Classifiers with Watson Visual Recognition
This module delves deeper into IBM Watson's image classifiers. You will learn to create a custom classifier in your Visual Recognition Instance and will train and test your custom classifier to classify dog images into different breeds.
Image Processing using IBM Watson and Python
This week, you will learn about image processing and face detection. You will then use Python and the Watson Visual Recognition API to perform image classification.
Face Detection and Image Processing using OpenCV and Python
This week, you will learn how to use the Haar Cascade classifiers for detecting eyes and faces in images. You will then do a variety of hands-on labs that will teach you how to perform license plate recognition using the Tesseract OCR, colour quantization, image compression, and image processing. While completing these labs, you will also learn how to use the OpenCV package in Python
Project: Building a Web-Based Computer Vision App
In the final week of this course, you will build a computer vision app that you will deploy on the web. For the project, you will create a custom classifier, train it and connect it to your app. You will then deploy your app to the cloud for making it accessible to anyone around the globe!
Лучшие отзывы о курсе Introduction to Computer Vision with Watson and OpenCV
This is one of the best course by IBM. I specifically enjoyed Computer Vision modelling and its related project and also enjoyed the way team put in effort for designing this course.
Great introduction to Visual Recognition and Computer Vision! Lots of examples are provided for me to grasp the concepts behind complicated applications!
Преподаватели
Yi Leng Yao
MSc., Data Scientist, Software Engineer
Sacchit Chadha
Software Engineer @ IBM | Rising Computer Science Senior @ UWaterlooО IBM
Профессиональная сертификация 'IBM Applied AI': общие сведения
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на сертификацию?
Записавшись на курс, вы получите доступ ко всем курсам в сертификации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
What will I be able to do after completing this course?
After completing this course you will be able to:
● explain what computer vision is and its applications
● understand the roles of Python, OpenCV and IBM Watson in computer vision
● classify images utilizing IBM Watson, Python, and OpenCV
● build and train custom image classifiers using Watson Visual Recognition API
● process images in Python using OpenCV
● create an interactive computer vision web application and deploy it to the cloud
Are there any software or hardware pre-requistes for this course?
No specialized hardware or software is required to complete this course. You will perform all labs and projects in a cloud environment and work with Python in Jupyter Notebooks, OpenCV, and IBM Watson Visual Recognition. Instructions for no-charge access to IBM Cloud is provided. You will require a modern web browser (i.e. recent versions of Chrome or Firefox).
Are there any pre-requisties or prior experience necssary for this course?
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