Analyze and Apply Deep Learning for Computer Vision

位教师：EDUCBA

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2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Analyze deep learning architectures and apply neural networks to visual data.
Implement computer vision techniques such as detection, segmentation, and image generation.
Evaluate and select appropriate models and workflows for real-world visual intelligence problems.

您将获得的技能

Recurrent Neural Networks (RNNs)
Artificial Intelligence and Machine Learning (AI/ML)
Generative AI
Transfer Learning
Computer Vision
Model Evaluation
Generative Model Architectures
Data Processing
Network Architecture
Artificial Neural Networks
Applied Machine Learning
Deep Learning
Feature Engineering
Image Analysis
Convolutional Neural Networks
技能部分已折叠。显示 7 项技能，共 15 项。

要了解的详细信息

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作业

7 项作业

授课语言：英语（English）

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该课程共有2个模块

By the end of this course, learners will be able to analyze core deep learning architectures, apply neural networks to visual data, and evaluate computer vision techniques for real-world problem solving. Learners will develop the ability to interpret how models learn from images, select appropriate architectures for specific tasks, and implement solutions for visual understanding and generation.

This course integrates foundational deep learning concepts with practical computer vision applications, enabling learners to move seamlessly from theory to implementation. Starting with neural networks, convolutional and recurrent architectures, learners build a strong conceptual base before advancing to image processing, feature extraction, object detection, segmentation, and image generation. Emphasis is placed on modern workflows such as transfer learning and generative modeling to reflect current industry practices. What makes this course unique is its end-to-end structure that connects deep learning fundamentals directly to visual intelligence use cases. Rather than treating deep learning and computer vision as separate disciplines, the course unifies them into a single, coherent learning journey. This approach equips learners with job-ready skills applicable to AI development, data science, and computer vision roles across industries.

This module introduces the fundamental principles of deep learning that underpin modern artificial intelligence systems, with a focus on neural network architectures, learning mechanisms, and advanced paradigms used in visual intelligence applications.

涵盖的内容

6个视频4个作业

6个视频总计84分钟

Neural Networks Basics 15分钟
Deep Learning Introduction 8分钟
Convolutional Neural Networks (CNNs) 14分钟
Recurrent Neural Networks (RNN) 20分钟
Generative Models 19分钟
Transfer Learning and Fine Tuning 9分钟

4个作业总计60分钟

Foundations of Deep Learning for Visual Intelligence 30分钟
Neural Network Fundamentals 10分钟
Deep Learning Architectures 10分钟
Advanced Learning Paradigms 10分钟

This module focuses on applying deep learning techniques to computer vision tasks, covering image preprocessing, feature extraction, object detection, image segmentation, and visual content generation in real-world scenarios.