Deep Learning with Python: Convolutional Neural Networks
1h 35mIntermediate2025-06-20
Authors
Frederick Nwanganga
Information Technology Professional and Teacher
Course details
Explore the fascinating world of convolutional neural networks (CNNs) and uncover how they’ve revolutionized the field of computer vision and deep learning. Understand the building blocks of CNNs and delve into practical exercises using Python, focusing on real-world applications such as image classification, object detection, and image segmentation. Instructor Fred Nwanganga helps you develop proficiency in designing, implementing, and optimizing CNN models. Enhance your understanding of sophisticated architectures like VGG Net, ResNet, and EfficientNet, and discover how to apply pretrained models for enhanced accuracy and efficiency. Designed for data scientists, machine learning enthusiasts, and developers with a foundational understanding of deep learning and Python coding skills, this course helps you unlock advanced machine learning techniques.
Learning objectives
Gain an understanding of computer vision, computer vision applications, the architecture of convolutional neural networks (CNN), and how to build a CNN in Python.
Apply advanced CNN architectures in a variety of different contexts.
Use CNNs to solve several computer vision problems in Python.
Learning objectives
Gain an understanding of computer vision, computer vision applications, the architecture of convolutional neural networks (CNN), and how to build a CNN in Python.
Apply advanced CNN architectures in a variety of different contexts.
Use CNNs to solve several computer vision problems in Python.
Skills covered
Deep Learning and Neural NetworksTraditional AI and Machine LearningPythonArtificial Intelligence (AI)Programming LanguagesOpen SourceSoftware DevelopmentOne-Off
Concepts
Introduction
- Using convolutional neural networks (CNNs) with Python
- What you should know
- Using the exercise files
Computer Vision
- What is computer vision
- A brief history of computer vision
- Understanding image data
- Preprocessing image data in Python
- Augmenting image data in Python
CNNs
- CNNs
- Convolutional layers and filters
- Pooling layers
- Fully connected layers
- Why are CNNs so effective for computer vision
Image Classification with CNNs
- Preparing to build a CNN in Python
- Defining a CNN in Python
- Training a CNN in Python
CNN Architectures
- VGGNet
- Inception networks
- ResNet
- MobileNet
- EfficientNet
Common Computer Vision Tasks
- What is image classification
- Using a pretrained model for image classification in Python
- What is object detection
- Using a pretrained model for object detection in Python
- What is image segmentation
- Using a pretrained model for image segmentation in Python
Conclusion
- Continuing with deep learning