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Generative AI with Python and TensorFlow 2
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Explore generative AI with Python and TensorFlow 2, mastering advanced algorithms, implementing models, and leveraging cloud resources to future-proof your skills and lead the GenAI revolution.
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Overview
With recent improvements in machine learning and deep learning, generative modeling has seen a tremendous uptick in the number of research works and its applications across different areas. Some of the newer methods (such as GANs) are very powerful yet difficult to control, making the overall learning process both exciting and frustrating.
In this course, you’ll explore generative AI, a cutting-edge technology for generating synthetic (yet strikingly realistic) data using advanced machine learning algori...Show More
With recent improvements in machine learning and deep learning, generative modeling has seen a tremendous uptick in the number o...Show More
WHAT YOU'LL LEARN
An understanding of generative models, including their applications, principles of probability, and various techniques used in generative AI
Working knowledge of deep learning, including perceptrons, backpropagation, convolutional neural networks (CNNs), and recurrent neural networks (RNNs)
Hands-on experience implementing generative AI models using TensorFlow 2
Familiarity with emerging applications of generative AI
An understanding of generative models, including their applications, principles of probability, and various techniques used in generative AI
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TAKEAWAY SKILLS
TensorFlow
Python
Generative AI
Content
103 Lessons11 Quizzes2 Assessments
1.
Introduction to the Course
1 Lessons
Get familiar with generative AI fundamentals, focusing on GANs, VAEs, and practical applications.
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Frequently Asked Questions
Can I use TensorFlow for generative AI?
Yes, you can use TensorFlow for generative AI by implementing models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) to generate new data, such as images, text, and music.
What is GAN in AI?
GAN (Generative Adversarial Network) in AI is a framework consisting of two neural networks, a generator and a discriminator, that compete to generate realistic data samples and distinguish between real and fake data.
