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Course Outline
Deep Learning vs. Machine Learning vs. Other Approaches
- Scenarios where Deep Learning is most effective
- Limitations of Deep Learning
- Comparative analysis of accuracy and cost across different methods
Methodological Overview
- Understanding Nets and Layers
- Forward and Backward Passes: The core computations in layered compositional models.
- Loss Functions: Defining the learning objective through loss.
- Solvers: Coordinating model optimization.
- Layer Catalogue: Layers serve as the fundamental units of modeling and computation.
- Convolutional Operations
Algorithms and Architectures
- Backpropagation and modular model designs
- Logsum modules
- RBF Networks
- MAP/MLE loss criteria
- Parameter Space Transforms
- Convolutional Modules
- Gradient-Based Learning
- Energy-based Inference
- Learning Objectives
- PCA and Negative Log-Likelihood (NLL)
- Latent Variable Models
- Probabilistic Latent Variable Models
- Loss Function Design
- Object Detection using Fast R-CNN
- Sequence Modeling with LSTMs and Vision-Language Integration with LRCN
- Pixel-wise Prediction using Fully Convolutional Networks (FCNs)
- Framework Architecture and Future Directions
Software Tools
- Caffe
- TensorFlow
- R
- Matlab
- Other tools
Requirements
Proficiency in any programming language is required. While prior knowledge of Machine Learning is not mandatory, it is advantageous.
21 Hours
Testimonials (3)
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
Nola - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
It felt like we were going through directly relevant information at a good pace (i.e. no filler material)
