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Analyze Visual Data with Machine Learning.
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A comprehensive list of all sections & lectures for this course can be found below.
Course Prerequisite: Machine Learning - Fundamentals - 00:00
What is Keras? Why use it? - 08:02
What is a Convolutional Neural Network (CNN)? - 26:30
Installing Keras with Anaconda - 04:38
Preparing Dataset for a CNN - 17:38
Building / Visualizing a CNN using Sequential: Part 1 - 14:07
Building / Visualizing a CNN using Sequential: Part 2 - 19:41
Training CNN / Evaluating Accuracy / Saving to Disk - 17:54
Switching Python Environments / Converting to Core ML Model - 13:39
Next Course: Build a Handwriting Recognition App using CoreML - 00:00
Course Prerequisite - Machine Learning Fundamentals
In this course, students will learn to build Convolutional Neural Networks using Machine Learning. The course begins with an introduction in Keras - a powerful easy-to-use Python library for developing and evaluating deep learning models.
Convolutional Neural Networks (CNN) - "is a class of deep neural networks, most commonly applied to analyzing visual imagery. They are also known as shift invariant or space invariant artificial neural networks, based on their shared-weights architecture and translation invariance characteristics." - Wikipedia
Students will learn to work with datasets to build a CNN using Sequential. The course also explores training and evaluating CNN, while evaluating accuracy.
Lastly, students will explore switching Python Environments, and converting to the Core ML Model.
All course reviews are written by students who have completed the course or are currently enrolled.
Thank you for this course. Very clear, detailed instruction.
Taking this course to further my studies on neural networks. The instructor is great, and there is a lot of information packed into 2 hours. Great job. Looking forward to completing the modules and taking the advanced courses as well.
great course. Took part one for the basics. Now this is much more advanced level.
I feel like i am beginning to understand neural networks. Although all this is fairly new, so it will probably take many more courses to fully understand the potential. Look forward to more from this instructor.
Very good instruction on a very complex topic! Highly recommend this course if you are interesting in constructing deep learning models using visualization.
Wow this course was thrilling. Very intense, but totally worth it. I've been wanting to learn about CNN for a while, but took me some time to make sense of it all. Thank you!
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