We observed the first wave of digital transformation in many sectors during COVID-19. The education sector also started to transform into digital by quickly adding more functionalities to their existing digital portals and introducing online teaching. Now I can see that with the introduction of ChatGPT, the education sector is going through the second wave of its transformation. Every academic institution is now concerned about academic integrity and how to respond to this change. I am also thinking about this challenge as I hear conversations from different parties…yet thinking from a different perspective and a different time frame 🙂
Author: Malmi Amadoru
Scientific Knowledge Construction in the Era of AI Agents!
Lot of us seem to be studying how new technologies like AI impact the way we live and work, and new methods to aid the scientific knowledge construction process. But what about the way we do research? Has anyone thought about how automated and AI-mediated content generation would affect the scientific method of discovery or […]
Enchanted Tour to North Island New Zealand
Kia Ora! I start my post by wishing in Maori language ‘be well and healthy‘ (it also means hello) as the sacred land of New Zealand belongs to them (I’ve heard from New Zealanders there had been a different indigenous tribe even before Maori, but I haven’t followed it up). New Zealand got the most […]
Introduction to Topic Modeling
Topic modeling is both an unsupervised machine learning and natural language processing technique capable of identifying topics out of a large corpus of documents. In other words it can create topic clusters from a large document collection. It can be used in many applications particularly in discourse analysis. Latent Dirichlet Allocation (LDA) is one of […]
Extending Linear Regression Models
Linear regression models assume the relationship between predictor variables and output variable is linear. Although linear models are simple and easy to interpret, it lacks predictive power because the true relationship is rarely linear. Ridge regression, lasso, and principle component regression are improved linear models with better model fitting. Yet, still those methods use a […]
Model Fitting in Linear Regression Setting
Model fitting refers to assessing the accuracy of the model. It is achieved by quantifying the extent to which model fits the data. The most common method in computing regression coefficients for model fitting is “least squares.” However to improve prediction accuracy and model interpretability, there are alternative model fitting methods too. Prediction Accuracy When […]
An Overview of Contemporary Classification Methods
Classification methods are used when the output variable is qualitative. Predicting a qualitative outcome for an observation is referred to as ‘classifying’. Figure 1 presents some of the most widely used classification methods. 1. Logistic Regression Logistic regression models the probability that an output variable (Y) belongs to a particular category. For example if you […]
Resampling Techniques
Resampling is the process of drawing samples repeatedly from a training data set and refitting the model on each sample to get additional information to decide on the best fit. The two of the most widely used techniques are cross-validation and bootstrap. 1. Cross-Validation Cross-validation is used to estimate the test error to evaluate model […]
Multiple Linear Regression
Multiple regression is used when there are more than one predictors or input variables. It extends the simple linear regression model by giving each predictor a separate slope coefficient within a single model. Given the number of predictors p equation is is the average effect on Y by increasing one of , holding all […]
Simple Linear Regression
Linear regression is a simple supervised learning approach for dealing with quantitative outcome variables. Mathematically simple linear regression which only includes a single input or predictor variable (X) is represented as; & are called model coefficients or model parameters. represents the intercept and represents the slope. is the mean-zero random error term. That is […]