Back to Building Deep Learning Models with TensorFlow
Learner Reviews & Feedback for Building Deep Learning Models with TensorFlow by IBM
844 ratings
About the Course
Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry.
You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality.
You will develop advanced convolutional neural networks (CNNs) using Keras. You will also build transformer models for sequential data and time series using TensorFlow with Keras. The course also covers the principles of unsupervised learning in Keras and TensorFlow for model optimization and custom training loops. Finally, you will develop and train deep Q-networks (DQNs) with Keras for advanced reinforcement learning tasks.
You will be able to practice the concepts learned in the hands-on labs after each lesson. A culminating final project in the last module will provide you an opportunity to apply your knowledge to build a Regression Model in Keras.
This course is suitable for all aspiring AI engineers who want to learn TensorFlow and Keras. It requires some basic knowledge of Python programming and basic mathematical concepts such as gradients and matrices.
Top reviews
MB
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The detail of prsenetation is awsome and make learning interesting. Thank you Corseara, Thank you IBM
ZR
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Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!
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