Introduction Reinforcement Learning (RL) is a powerful framework that enables agents to learn optimal behaviours through interaction with an environment. From mastering complex games like Go to...
![Policy Gradient [Reinforcement Learning] Made Simple In An Elaborate Guide](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/11/q-learning-explained.jpg?fit=1200%2C675&ssl=1)
The Natural Language Processing (NLP) Blog
Topic: Learning Types
![Deep Q-Learning [Reinforcement Learning] Explained & How To Example](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2025/05/q-learning-example.jpg?fit=1440%2C810&ssl=1)
Deep Q-Learning [Reinforcement Learning] Explained & How To Example
Imagine teaching a robot to navigate a maze or training an AI to master a video game without ever giving it explicit instructions—only rewarding it when it does something right. This is the essence...
Federated Learning Made Simple, Why its Important & Application in the Real World
What is Federated Learning? Federated Learning (FL) is a cutting-edge machine learning approach emphasising privacy and decentralisation. Unlike traditional machine learning methods, which rely on...
NLP And Edge Computing: How It Works & Top 7 Technologies for Offline Computing
In the age of digital transformation, Natural Language Processing (NLP) has emerged as a cornerstone of intelligent applications. From chatbots and voice assistants to real-time translation and...
Out-of-Distribution In Machine Learning Made Simple & How To Detect It
What is Out-of-Distribution Detection? Out-of-Distribution (OOD) detection refers to identifying data that differs significantly from the distribution on which a machine learning model was trained,...
![Anomaly Detection In LLM Responses [How To Monitor & Mitigate]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/11/types-of-anomalies-llms.jpg?fit=1200%2C675&ssl=1)
Anomaly Detection In LLM Responses [How To Monitor & Mitigate]
What is Anomaly Detection in LLMs? Anomaly detection in the context of Large Language Models (LLMs) involves identifying outputs, patterns, or behaviours that deviate significantly from what is...
Predictive Analytics Made Simple & How To Python Tutorial
What is Predictive Analytics? Predictive analytics uses historical data, statistical algorithms, and machine learning techniques to identify patterns and forecast future outcomes. At its core, it...
![Understand Ordinary Least Squares: How To Beginner’s Guide [Tutorials In Python, R & Excell]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/08/ordinary-least-square.jpg?fit=1200%2C675&ssl=1)
Understand Ordinary Least Squares: How To Beginner’s Guide [Tutorials In Python, R & Excell]
What is Ordinary Least Squares (OLS)? Ordinary Least Squares (OLS) is a fundamental technique in statistics and econometrics used to estimate the parameters of a linear regression model. In simple...
![Bias Mitigation in Machine Learning [Practical How-To Guide & 12 Strategies]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/05/techniques-bias-detection.jpg?fit=1440%2C810&ssl=1)
Bias Mitigation in Machine Learning [Practical How-To Guide & 12 Strategies]
In machine learning (ML), bias is not just a technical concern—it's a pressing ethical issue with profound implications. As AI systems become increasingly integrated into our daily lives, from...
Online Machine Learning Explained & How To Build A Powerful Adaptive Model
What is Online Machine Learning? Online machine learning, also known as incremental or streaming learning, is a type of machine learning in which models are updated continuously as new data becomes...
![Bagging, Boosting & Stacking Made Simple [3 How To Tutorials In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/03/bagging-boosting-stacking.jpg?fit=1200%2C675&ssl=1)
Bagging, Boosting & Stacking Made Simple [3 How To Tutorials In Python]
What is Bagging, Boosting and Stacking? Bagging, boosting and stacking represent three distinct ensemble learning techniques used to enhance the performance of machine learning models. Bagging,...
![Bayesian Network Made Simple [How It Is Used In Artificial Intelligence & Machine Learning]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/02/bayesian-netowork-node-edges.jpg?fit=1920%2C1080&ssl=1)
Bayesian Network Made Simple [How It Is Used In Artificial Intelligence & Machine Learning]
What is a Bayesian Network? Bayesian network, also known as belief networks or Bayes nets, are probabilistic graphical models representing random variables and their conditional dependencies via a...
![Knowledge Graph Reasoning Made Simple [3 Technical Methods & How To Handle Uncertanty]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/02/query2vec.jpg?fit=1200%2C675&ssl=1)
Knowledge Graph Reasoning Made Simple [3 Technical Methods & How To Handle Uncertanty]
What is Knowledge Graph Reasoning? Knowledge Graph Reasoning refers to drawing logical inferences, making deductions, and uncovering implicit information within a knowledge graph. A knowledge graph...
Computational Linguistics: An Easy Explanation With Examples, Advancements & Future Trends
What is Computational Linguistics? Computational linguistics is an interdisciplinary field that combines principles of linguistics and computer science to develop computational models and algorithms...
Knowledge Representation And Reasoning In Artificial Intelligence (AI) Made Simple
What is Knowledge Representation and Reasoning (KRR)? Knowledge Representation and Reasoning (KRR) are fundamental concepts in artificial intelligence (AI) that focus on how intelligent systems can...
![Semi-Supervised Machine Learning Made Simple [5 Algorithms & How To Python Tutorial]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/semi-supervised-machine-learning.jpg?fit=1200%2C675&ssl=1)
Semi-Supervised Machine Learning Made Simple [5 Algorithms & How To Python Tutorial]
What is Semi-Supervised Learning in Machine Learning? Semi-supervised learning is a machine learning paradigm between supervised and unsupervised learning. In this approach, the algorithm learns...
Embeddings from Language Models (ELMo): Contextual Embeddings A Powerful Shift In NLP
What are Embeddings from Language Models (ELMo)? ELMo, short for Embeddings from Language Models, revolutionized the landscape of NLP by introducing contextual embeddings, a paradigm shift from...
Data2vec Explained: The Fusion Of Text, Image & Audio To Create Powerful AI Systems
What is Data2vec? Meta AI has introduced Data2vec, a groundbreaking framework for self-supervised learning that transcends the barriers between different data modalities. Data2vec proposes a unified...
