- eBook:Introduction to Deep Learning for Engineers: Using Python and Google Cloud Platform
- Author:Tariq M. Arif
- Data:July 22, 2020
- Pages:110 pages
In recent years, deep learning-based modeling approaches have been used in a wide variety of engineering domains, such as autonomous cars, intelligent robotics, computer vision, natural language processing, and bioinformatics. Also, numerous real-world engineering applications utilize an existing pre-trained deep learning model that has already been developed and optimized for a related task. However, incorporating a deep learning model in a research project is quite challenging, especially for someone who doesn't have related machine learning and cloud computing knowledge. Keeping that in mind, this book is intended to be a short introduction of deep learning basics through the example of a practical implementation case.
The audience of this short book is undergraduate engineering students who wish to explore deep learning models in their class project or senior design project without having a full journey through the machine learning theories. The case study part at the end also provides a cost-effective and step-by-step approach that can be replicated by others easily.
2. Introduction to PyTorch
3. Basic Artificial Neural Network and Architectures
4. Introduction to Deep Learning
5. Deep Transfer Learning
6. Setting Up PyTorch and Google Cloud Platform Console
7. Case Study: Practical Implementation Through Transfer Learning
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