Computer Vision and Image Processing - Intro
Learn to apply image processing, analysis methods, and supervised learning techniques using Python, Pillow, and OpenCV to address computer vision issues across various industries.
Description for Computer Vision and Image Processing - Intro
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by IBM
Duration: 21 hours (approximately)
Schedule: Flexible
Pricing for Computer Vision and Image Processing - Intro
Use Cases for Computer Vision and Image Processing - Intro
FAQs for Computer Vision and Image Processing - Intro
Reviews for Computer Vision and Image Processing - Intro
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Computer Vision and Image Processing - Intro
In-depth study of the applications of machine learning and computer vision, as well as practical experience in data analysis and Python programming.
Develop your skills in image processing, augmented reality, and object recognition to prepare yourself to create cutting-edge AI-powered visual apps.
Learn to apply advanced machine learning and deep learning models to real-world challenges by immersing yourself in the cutting-edge world of AI-powered finance and insurance.
Exploration of the implementation of AI and machine learning in constrained environments and Arm microcontrollers.
The program provides students with the knowledge and abilities to differentiate between AI technologies, host models on Amazon Sagemaker, and apply AI and machine learning to real-world activities.
The course gives an extensive understanding of AI, which encompasses its ethical implications, neural networks, data significance, and applications.
Using the complete machine learning pipeline in computer vision, this course teaches students how to use MATLAB for object detection and classification in images.
Brief Summary This course analyzes the deployment of machine learning models on Arm microcontrollers, with an emphasis on real-world applications in edge computing.
In this course, the main business applications of AI/ML are introduced, with an emphasis on tool selection and ethical behavior.
Develop an understanding of the machine learning protocol, which encompasses the entire process from data preparation and model training to the dissemination of results to the organization.
Featured Tools
Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.
Discover AI terminology, ethical norms, and protocols for responsibly utilizing and citing Generative AI.
A practical guide to the use of generative AI for the purpose of composing, refining, and planning, utilizing structured and context-driven inputs.
Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.
An extensive study of the applications of AI in marketing, ranging from competitive analysis to content optimization and conversion enhancement.