How to Conduct a Literature Review in AI & Machine Learning
Author(s): Ayo Akinkugbe Originally published on Towards AI. A Technical Guide to Surveying, Synthesizing, and Positioning Your AI Research Photo by Kristine Wook on Unsplash What’s So Lit About a Lit Review? A literature review is the backbone of any meaningful research …
How to Craft a Strong AI/ML Thesis Statement
Author(s): Ayo Akinkugbe Originally published on Towards AI. Defining Scope, Hypotheses, and Contribution Boundaries for Clarity, Testability, and Impact in AI & ML Research Photo by Omar:. Lopez-Rincon on Unsplash Snapshot A thesis statement is the central claim of your dissertation or …
How to Identify AI & ML Research Problems Worth Solving
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Julius Carmine on Unsplash In Search of a North Star Formulating a research question is one of the early and most important steps in the research process. It is the one determinant …
Why and How We t-Test
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Girl with red hat on Unsplash Introduction When running experiments — be it with models, prompts, or human evaluations — we often need to answer one deceptively simple question: Did the change …
Discrete Time System Properties- Plainly
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Valentin Salja on Unsplash Seeing the Future When I first saw terms like causal, stable, linear, and time-invariant, I thought: here comes another wall of jargon. But after working through some examples, …
The Generative AI Model Map
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Jackson Simmer on Unsplash Introduction With the commercialization of the GPT model in 2022, generative AI (artificial intelligence) became popular. However large language models — the category of generative models GPT belongs …
Kernels: A Deep Dive
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Girl with red hat on Unsplash Introduction: What are Kernels A kernel is a smart way to measure similarity between two things — in particular, data points, images, text documents, or more …
The Essential Guide to ML Evaluation Metrics for Regression
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Europeana on Unsplash Introduction Machine learning models are only as good as our ability to measure them. Though a perfect model isn’t always possible, a good enough model is. But how do …
The Essential Guide to Model Evaluation Metrics for Classification
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Europeana on Unsplash Introduction Classification is one of the most common machine learning tasks, where models predict discrete categories or classes. Examples include detecting fraud, diagnosing diseases, or filtering spam emails. To …
Task Arithmetic for Model Editing
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by charlesdeluvio on Unsplash Introduction In the 2004 film “Eternal Sunshine of the Spotless Mind,” Clementine (played by Kate Winslet) and Joel (played by Jim Carey) visit Lacuna Inc. to undergo a revolutionary …
An Essential Guide for Generative Models Evaluation Metrics
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Europeana on Unsplash Introduction Generative models are everywhere – The most popular being LLMs. However generative tasks span generating realistic photos (eg. GANs, Diffusion models), to creating text (eg. large language models), …
The Generative AI Model Map
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Jackson Simmer on Unsplash Introduction With the commercialization of the GPT model in 2022, generative AI (artificial intelligence) became popular. However large language models — the category of generative models GPT belongs …
Understanding Convolution
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by David Becker on Unsplash To better understand what convolution is, it is needful to know why dense neural networks (DNN) don’t work well for images. If you trained a DNN and a …
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