Artificial Intelligence Foundations: Neural Networks
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Gwendolyn Stripling
1:45:18
107 View
01 - Neural networks 101 Your path to AI brilliance.mp4
00:53
02 - What you should know.mp4
00:42
03 - How to use the challenge exercise files.mp4
01:37
01 - Machine learning and neural networks.mp4
04:55
02 - Biological neural networks.mp4
02:33
03 - Artificial neural networks.mp4
01:52
04 - Single-layer perceptron.mp4
04:12
01 - Multilayer perceptron.mp4
04:07
02 - Layers Input, hidden, and output.mp4
02:55
03 - Transfer and activation functions.mp4
03:41
04 - How neural networks learn.mp4
05:39
01 - Convolutional neural networks (CNN).mp4
09:16
02 - Recurrent neural networks (RNN).mp4
07:55
03 - Transformer architecture.mp4
04:27
01 - The Keras Sequential model.mp4
04:20
02 - Use case and determine evaluation metric.mp4
05:25
03 - Data checks and data preparation.mp4
02:48
04 - Data preprocessing.mp4
02:11
05 - Train the neural network using Keras.mp4
06:26
06 - Challenge Build a neural network.mp4
00:51
07 - Solution Build a neural network.mp4
04:04
01 - Overfitting and underfitting Two common ANN problems.mp4
04:54
02 - Hyperparameters and neural networks.mp4
03:24
03 - How do you improve model performance.mp4
03:56
04 - Regularization techniques to improve overfitting models.mp4
07:40
05 - Challenge Manually tune hyperparameters.mp4
00:45
06 - Solution Manually tune hyperparameters.mp4
02:04
01 - Next steps.mp4
01:46
Description
An artificial neural network uses the human brain as inspiration for creating a complex machine learning system. They can classify millions of sounds, videos, and images, answer our questions, understand our behaviors, and even drive our cars. Neural networks are also the foundation of generative AI.
This course introduces the fundamental techniques and principles of neural networks, common models, and their applications. Instructor Gwendolyn Stripling takes you through the different neural network architectures, their components, appropriate use cases, and best practices for improving neural network model performance. Plus, gain hands-on experience building and training a neural network using the Keras Sequential API, an open-source library that demystifies the design and training of neural networks. If you’re looking to achieve a solid understanding of how to build, train, improve and use neural networks, join Gwendolyn in this course.More details
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Gwendolyn Stripling
Instructor's Courses
Linkedin Learning
View courses Linkedin LearningLinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications.
It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.
- language english
- Training sessions 28
- duration 1:45:18
- English subtitles has
- Release Date 2023/11/16
