Deep Learning is a key technology driving the artificial intelligence (AI) megatrend. You may have heard of some of the mainstream applications of deep learning, but how many of them would you consider applying to your engineering and science applications?
MathWorks developers have applied deep learning functions in MATLAB® to engineering and science workflows. In this series of videos, you will learn how to use MATLAB to harness the power of disruptive technologies like deep learning.
In the latter videos, you will delve into more advanced topics like:
Finally, you will learn how to set up your own experiments and tune convolutional neural networks.
Part 1: Deep Learning Overview for Images and Video See how to use MATLAB to exploit disruptive technology such as deep learning, with a focus on signals and time series data.
Part 2: Deep Learning Overview for Signals and Timeseries See how to use MATLAB to exploit disruptive technology such as deep learning, with a focus on signals and time series data.
Part 3: Deep Learning Overview for Control Systems (using Reinforcement Learning) Learn how to perform reinforcement learning using MathWorks products, including how to set up environment models, define the policy structure, and scale training through parallel computing to improve performance.
Part 4: Automated Optical Inspection and Defect Detection with Deep Learning Learn how to use MATLAB to develop deep learning-based approaches to detect and localize different types of anomalies.
Part 5: The Key Role of Data in Modern AI-Powered Systems - Spotting Voice Keywords and Beyond Using MATLAB code, explore what it takes to make a device selectively wake up with trigger phrases like "Hey Siri" or "OK Google."
Part 6: Deep Learning Overview for Medical Images Deep learning is a principle technology enabling remarkable advancements in AI. While you may be aware of mainstream applications of deep learning, how well acquainted are you with AI applications in medical engineering and science?
Part 7: A Deep Dive into Deep Learning Modeling – Designing Experiments See how MATLAB deep learning apps can help you edit neural networks and devise and run experiments
Part 8: A Deep Dive into Deep Learning Modeling – Advanced Neural Networks Learn about the extended deep learning framework in MATLAB, which enables you to implement advanced network architectures such as generative adversarial networks (GANs), variational autoencoders (VAEs), or Siamese networks