Welcome to the tutorials section on deep learning within the Data Sciences community of the ABC Compute Forum. Here, you will find a variety of resources to help you understand and master the intricacies of deep learning.
Tutorials Overview
- Neural Networks Basics: Learn the fundamentals of neural networks.
- Convolutional Neural Networks (CNNs): Explore CNNs for image recognition and processing.
- Recurrent Neural Networks (RNNs): Understand how RNNs handle sequential data.
- Generative Adversarial Networks (GANs): Discover the power of GANs in generating realistic data.
- Transfer Learning: Learn how to leverage pre-trained models for your projects.
Resources
- Neural Networks Basics
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Generative Adversarial Networks (GANs)
- Transfer Learning
Case Study
Let's say you're interested in image recognition. You might start with the Convolutional Neural Networks (CNNs) tutorial. Here, you'll learn how to build a simple CNN using TensorFlow and Keras.
CNNs in Practice
CNNs are particularly effective for image recognition tasks. They automatically and adaptively learn spatial hierarchies of features from input images.
By the end of the tutorial, you'll be able to classify images into different categories using a pre-trained CNN model.
Join the Discussion
If you have any questions or need further assistance, feel free to join the Deep Learning Forum to discuss with fellow learners and experts.