Artificial Intelligence

AI Learning Types - Reinforcement Learning

In reinforcement learning, AI systems learn by interacting with their environment and receiving feedback in the form of rewards or penalties. The AI system aims to maximise the cumulative reward over time by choosing the optimal sequence of actions.

AI Learning Types - Transfer Learning

Transfer learning is a technique in machine learning where a model trained on one task is repurposed on a related task, leveraging the knowledge it has already gained to improve learning efficiency and performance.

AI Learning Types - Unsupervised Learning

Unsupervised learning can find interesting patterns in your data

AI basics

10 things you need to know about Artificial Intelligence

Natural Language Processing: A Key Component of AI

Natural Language Processing (NLP) is a subfield of AI that focuses on understanding and generating human language. It encompasses tasks like text analysis, machine translation, and sentiment analysis, transforming how we interact with technology and opening up new possibilities.

Understanding Neural Networks in AI

AI vs. ML vs. RBL: The differences between Artificial Intelligence and Machine Learning and Rules Based Learning

Artificial intelligence and machine learning are two terms that are often used interchangeably, but they are actually quite different.

Training AI Systems - Learning Types

Learning Types refer to the fundamental ways in which an AI model learns from data. This category includes: Supervised Learning, Unsupervised Learning and Reinforcement Learning

Memory in Artificial Intelligence: The Key to Advanced Learning

Hyperparameter Tuning in AI: Enhancing Model Performance

Hyperparameter tuning optimises AI model performance by finding the best parameter settings. It improves accuracy, saves resources, and is crucial for AI development. It also prevents overfitting, where a model learns to perform exceptionally well on the training data but fails with new unseen data