Deep Learning Course Syllabus
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Deep learning is transforming a number of industries, including robots, healthcare, natural language processing, and computer vision. In addition to providing students with the knowledge and abilities to create and implement deep learning models for a variety of real-world problems, our syllabus for deep learning will examine the state-of-the-art uses of deep learning. Through practical projects, students will gain experience and learn about the most recent developments in deep learning in this deep learning course outline.
Course Syllabus
Download SyllabusIntroduction To Deep Learning
- What Exactly Is Deep Learning?
- Neural Network
- Supervised Learning With Neural Networks
- Prominence Of Deep Learning
Shallow Neural Networks
- Neural Networks Overview
- Neural Network Representation
- Vectorizing Across Multiple Example
- Derivatives Of Activation Functions
- Random Initialization
Neural Networks Basics
- Binary Classification
- Logistic Regression
- Gradient Descent
- Logistic Regression Gradient Descent
- Vectorization
Deep Neural Networks:
- Neural Networks Overview
- Neural Network Representation
- Vectorizing Across Multiple Example
- Derivatives Of Activation Functions
- Random Initialization
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