Visual Style Innovation - Master Image Transformation Techniques with Python ML
Have you ever seen a photo transformed into a painting and wondered how it’s done?
If you’re intrigued by the process of image style transfer, this course is perfect for you!
Dive into the world of machine learning and discover how to build a Python model that changes the style of an image, turning your photos into artistic masterpieces.
Plus, take on an additional project where you'll use machine learning to closely replicate an image through approximation.
This course offers a fun and hands-on approach to mastering these creative techniques, making it the ideal way to enhance your skills and explore the possibilities of AI-driven art!
Your Instructor
Jared Matson graduated from the University of Alberta with a degree in Computer Science. While at university, he discovered a knack for web design and enjoys spending his spare time building websites for small businesses using vanilla HTML, CSS, PHP, and JavaScript.
Jared also enjoys working with various other tools and programming languages, such as Python for finance and machine learning, C# for game development, and Java.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider, and more.
Over 14 years, Mammoth Interactive has built a global student community with 8 million courses sold. Mammoth Interactive has released over 1,000 courses and 5,000 hours of video content.
Course Curriculum
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Start00 Style Transfer Project Overview (5:36)
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Start01 Load The Model (4:57)
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Start02 Load Images (6:53)
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Start03 Reformat Image For Machine Learning (7:03)
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Start04 Load Original And Style Images (6:27)
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Start05 Display Processed Images (10:58)
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Start06 Extract Image Features (6:59)
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Start07 Calculate The Style Representation (6:01)
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Start08 Optimize The Model (5:27)
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Start09 Use Machine Learning To Transfer Image Style (13:54)
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StartSource Files
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Start00 Load And Process Image (7:14)
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Start01 Build A Training Dataset (6:49)
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Start02 Visualize Training Dataset (5:36)
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Start03 Build A Testing Dataset (4:04)
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Start04 Build A Neural Network (7:25)
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Start05 Train The Neural Network (4:40)
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Start06 Visualize Image Approximation Results (5:14)
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StartSource Files