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Using Machine Learning – notes
Machine learning (ML) is a branch of artificial intelligence that enables systems to learn from data and improve performance without explicit programming. This field sits at the intersection of statistics and computer science, aiming to create models that identify...
Alternatives to Jira for Agile Software Development
Jira has long been a cornerstone for Agile software development teams, offering robust features for project management, issue tracking, and collaboration. However, its complexity and cost can be prohibitive for some teams, prompting the search for viable alternatives....
The History of AI: A Journey Through the Industrial Revolutions
I've been doing the Oxford Said Artificial Intelligence Programme. The module on the history of AI was particularly fascinating, perhaps because of my interest in science fiction. Here's a summary of what I learned. Officially coined by John McCarthy in 1956, AI has...
Why you should document your software and what to do if you haven’t
In software development, documentation is crucial for maintaining clarity and consistency across projects. Documenting software serves multiple purposes, such as preserving knowledge, facilitating collaboration, and enhancing future maintenance efforts. When software...
An Introduction to Q-Learning: The Fundamentals and Applications
Reinforcement learning (RL) has emerged as a pivotal subfield of machine learning, enabling computers to learn and make decisions through trial and error. One of the most widely utilised RL algorithms is Q-learning, a model-free technique that has garnered attention...
Understanding Architecture in Software Development
Architecture is a cornerstone discipline in software development that provides a structured framework for creating software systems. Much like architectural blueprints guide building construction, software architecture lays the groundwork for software development,...