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Applied Machine Learning: Techniques and Applications
Master practical machine learning techniques with focus on computer vision, data preprocessing, and model evaluation using industry tools.
Course Cost
Free course
Intermediate
Skill Level
17 Hours
Self-paced lessons
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Applied Machine Learning Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
English
What you'll learn
Implement machine learning techniques for computer vision tasks
Analyze data features and evaluate model performance
Apply effective data pre-processing methods
Develop supervised learning algorithms
Optimize model performance using evaluation metrics
Skills you'll gain
This course includes:
9.5 Hours PreRecorded video
12 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This comprehensive course focuses on practical applications of machine learning, particularly in computer vision and data analysis. Students learn essential techniques in data preprocessing, feature engineering, and model evaluation. The curriculum covers supervised learning algorithms, implementation of computer vision tasks, and hands-on experience with tools like Weka. Special emphasis is placed on real-world applications and practical implementation of machine learning concepts.
Application of Machine Learning in Computer Vision
Module 1 · 3 Hours to complete
Data Features & Model Evaluation
Module 2 · 4 Hours to complete
Data Pre-Processing
Module 3 · 3 Hours to complete
Supervised Learning
Module 4 · 6 Hours to complete
Fee Structure
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.