I developed a new course Software Engineering for Machine Learning (SER 594) that is being offered this Spring (2022).
This course: (a) presents frameworks and tools for developing and incorporating machine-learning components into software systems; and (b) examines the application, adaptation, and extension of software engineering practices to develop and adopt machine-learning-enabled robust, secure, and scalable systems.
Syllabus
Arizona State University.
School of Computing and Augmented Intelligence.
version Spring 2022
Lectures
This course will include 26 lectures:
- Course Presentation
- Fundamentals on Machine Learning
- Deep Learning
- Neural Networks
- Programming a Neural Network
- Working with DeepLearning4J
- Performance Measurement
- Image Recognition
- Image Recognition with DeepLearning4J
- Network Architecture
- Working with a Model
- Convolutional Neural Networks
- Midterm Review
- Unsupervised Learning
- Clustering Algorithms: K-means, DBSCAN, EM
- Clustering with Weka
- Text Mining: Latent Dirichlet Allocation
- Mallet: MAchine Learning for LanguagE Toolkit
- Text Mining Evaluation
- Spam Recognition
- Naive Bayes
- Decision Tree and Random Forest
- Final Review
Videos
Some lectures have been recorded and are available in my YouTube Channel