This workshop will introduce participants to Generative Adversarial Networks (GANs). We will demonstrate the core techniques of GANs, including how to use Deep Convolutional GANs (DCGANs) to generate images using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be…
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neural networks
Learning Convolutional Neural Networks (2)
This workshop will be the second lecture in our introduction to convolutional neural networks (CNNs). We will continue our learning by applying data augmentation and transfer learning techniques to improve our solution for the classic Dogs-vs-Cats problem using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with…
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Learning Convolutional Neural Networks (1)
This workshop will provide an introduction to convolutional neural networks (CNNs). We will begin by using PyTorch to perform image processing on the classic Dogs-vs-Cats problem. Basic knowledge of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be helpful for fully participating in the…
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Introduction to Neural Networks
This workshop is a descriptive “no-math” and “no-python” introduction to what deep learning is and how to train a deep neural network. Our discussion will be arranged along with a general procedure for working on a deep learning project. Basic knowledge of calculus and linear algebra will be helpful in understanding the details. Any questions…
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