Course Outline
Machine Learning Algorithms in Julia
Introductory Concepts
- Supervised and unsupervised learning
- Cross-validation and model selection
- Bias-variance trade-off
Linear and Logistic Regression
(NaiveBayes and GLM)
- Introductory concepts
- Fitting linear regression models
- Model diagnostics
- Naive Bayes
- Fitting a logistic regression model
- Model diagnostics
- Model selection methods
Distances
- What is a distance?
- Euclidean
- Cityblock
- Cosine
- Correlation
- Mahalanobis
- Hamming
- MAD
- RMS
- Mean squared deviation
Dimensionality Reduction
-
Principal Component Analysis (PCA)
- Linear PCA
- Kernel PCA
- Probabilistic PCA
- Independent Component Analysis (ICA)
- Multidimensional scaling
Altered Regression Methods
- Basic concepts of regularisation
- Ridge regression
- Lasso regression
- Principal Component Regression (PCR)
Clustering
- K-means
- K-medoids
- DBSCAN
- Hierarchical clustering
- Markov Cluster Algorithm
- Fuzzy C-means clustering
Standard Machine Learning Models
(NearestNeighbors, DecisionTree, LightGBM, XGBoost, EvoTrees, LIBSVM packages)
- Gradient boosting concepts
- K nearest neighbours (KNN)
- Decision tree models
- Random forest models
- XGBoost
- EvoTrees
- Support vector machines (SVM)
Artificial Neural Networks
(Flux package)
- Stochastic gradient descent and strategies
- Multilayer perceptrons: forward feed and backpropagation
- Regularisation
- Recurrent neural networks (RNN)
- Convolutional neural networks (Convnets)
- Autoencoders
- Hyperparameters
Requirements
This course is intended for participants who already have a background in data science and statistics.
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
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
