Fundamentals of CNNs and RNNs
This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas. In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs. The goal of this course is to give learners basic understanding of CNNs and RNNs.
Monthly Subscription Starting at AED 99 + VAT
- Level Foundation
- Duration 6 hours
- Course by Sungkyunkwan University
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Offered by
About
This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas. In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs. The goal of this course is to give learners basic understanding of CNNs and RNNs. Throughout this course, you will be equipped with skills required for computer vision and natural language processing.Modules
Week 1. CNN Basics
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Week 2. Convolution and Pooling
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Week 3. Structure of CNNs
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Week 4. Recurrent Neural Network
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Week5. LSTM GRU
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Auto Summary
Unlock the basics of CNNs and RNNs with this foundational course in Data Science & AI, guided by Coursera. Dive into key concepts, structures, and operators of CNNs and RNNs, including LSTMs and GRUs, essential for computer vision and natural language processing. Complete in 360 minutes with Starter and Professional subscription options. Perfect for beginners aiming to build expertise in AI.
Jee-Hyong Lee