Feb
6
5:30pm
Deep Learning Master Class II - Computer Vision
By IBM Developer
This series takes engineers from zero to expert in machine learning in 5 sessions. The world needs more people who understand machine learning, and our goal is to get you started on that path as efficiently as possible. While there are plenty of online resources, we know it's tough to learn a technical topic without a teacher. This workshop will arm you with the tools to get started using machine learning in your day job, and the resources to find additional help if you want to go deeper.
Part 2 - Introduction to Computer Vision
This class is part two of our series that takes engineers from zero to one in deep learning. It’s designed as a follow up to Technical Introduction to AI, Machine Learning & Deep Learning but could also be appropriate for someone who had done some machine learning and wanted to really focus on deep learning algorithms and computer vision.
We will look at the following frameworks and architectures
Deep Learning Frameworks
1. Numpy
2. TensorFlow
3. Keras
Deep Learning Model Architectures
1. Autoencoders
2. Convolutional Neural Networks
3. Adversarial Networks
4. Perceptron
5. MLPs
We will discuss some of the more popular application of computer vision including
1. Object detection
2. Image segmentation
3. Bounding Boxes
4. Building convolutional neural networks
5. Image Recognition
You can watch the previous sessions here:
1. Deep Learning Master Class I - Introduction - URL TBD
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