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Building Deep Learning Models with TensorFlow

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The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems.

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Embark on an advanced journey into the realm of Data Science and AI with the "Building Deep Learning Models with TensorFlow" course offered by Coursera. This professional-level course is meticulously designed to harness the power of deep learning for tackling the challenges posed by unlabeled and unstructured data, such as images, sound, and text. Guided by expert instructors, learners will delve into the TensorFlow library, mastering the skills needed to construct and implement deep neural networks that can uncover hidden structures within complex data sets. Over a comprehensive 420-minute duration, participants will gain hands-on experience in applying these techniques to solve tangible, real-world problems. With flexible subscription options including Starter and Professional plans, this course caters to those looking to elevate their expertise in deep learning and TensorFlow. Ideal for data science professionals and AI enthusiasts aiming to deepen their knowledge and practical skills, this course promises to be an invaluable asset in advancing your career in the ever-evolving field of artificial intelligence.