What are Ranking Algorithms? Ranking algorithms are computational processes used to order items, such as web pages, products, or multimedia content, based on their relevance or importance to a given...
The Natural Language Processing (NLP) Blog
Topic: Data Science
Ultimate Guide To Data Structure Hashing With How To Tutorial In Python
What is Hashing? Hashing is used in computer science as a data structure to store and retrieve data efficiently. At its core, hashing involves taking an input (or "key") and running it through a...
ROC And AUC Curves In Machine Learning Made Simple & How To Tutorial In Python
What are ROC and AUC Curves in Machine Learning? The ROC Curve The ROC (Receiver Operating Characteristic) curve is a graphical representation used to evaluate the performance of binary...
Naive Bayes Classification Made Simple & How To Tutorial In Python
What is Naive Bayes? Naive Bayes classifiers are a group of supervised learning algorithms based on applying Bayes' Theorem with a strong (naive) assumption that every feature in the dataset is...
How To Implement Anomaly Detection With One-Class SVM In Python
What is One-Class SVM? One-class SVM (Support Vector Machine) is a specialised form of the standard SVM tailored for unsupervised learning tasks, particularly anomaly detection. Unlike traditional...
![Decision Trees In ML Complete Guide [How To Tutorial, Examples, 5 Types & Alternatives]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/05/decision-tree-example.jpg?fit=1200%2C675&ssl=1)
Decision Trees In ML Complete Guide [How To Tutorial, Examples, 5 Types & Alternatives]
What are Decision Trees? Decision trees are versatile and intuitive machine learning models for classification and regression tasks. It represents decisions and their possible consequences,...
Isolation Forest For Anomaly Detection Made Easy & How To Tutorial
What is an Isolation Forest? Isolation Forest, often abbreviated as iForest, is a powerful and efficient algorithm designed explicitly for anomaly detection. Introduced by Fei Tony Liu, Kai Ming...
Batch Gradient Descent In Machine Learning Made Simple & How To Tutorial In Python
What is Batch Gradient Descent? Batch gradient descent is a fundamental optimization algorithm in machine learning and numerical optimisation tasks. It is a variation of the gradient descent...
Full-Text Search Explained, How To Implement & 6 Powerful Tools
What is Full-Text Search? Full-text search is a technique for efficiently and accurately retrieving textual data from large datasets. Unlike traditional search methods that rely on simple string...
Support Vector Regression (SVR) Simplified & How To Tutorial In Python
What is Support Vector Regression (SVR)? Support Vector Regression (SVR) is a machine learning technique for regression tasks. It extends the principles of Support Vector Machines (SVM) from...
Weight Decay In Machine Learning And Deep Learning Explained & How To Tutorial
What is Weight Decay in Machine Learning? Weight decay is a pivotal technique in machine learning, serving as a cornerstone for model regularisation. As algorithms become increasingly complex and...
![Collaborative Filtering In Machine Learning Made Simple [6 Different Approaches]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/user-based-collaborative-filtering.jpg?fit=1200%2C675&ssl=1)
Collaborative Filtering In Machine Learning Made Simple [6 Different Approaches]
What is Collaborative Filtering? In today's digital era, where we are inundated with overwhelming information and choices, recommendation systems have become indispensable. From suggesting movies to...
Data Drift In Machine Learning Explained: How To Detect & Mitigate It
What is Data Drift Machine Learning? In machine learning, the accuracy and effectiveness of models heavily rely on the quality and consistency of the data on which they are trained. However, in...
Classification Metrics In Machine Learning Explained & How To Tutorial In Python
What are Classification Metrics in Machine Learning? In machine learning, classification tasks are omnipresent. From spam detection in emails to medical diagnosis and sentiment analysis in social...
![Co-occurrence Matrices Explained: How To Use Them In NLP, Computer Vision & Recommendation Systems [6 Tools]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/co-occurance-matrix.jpg?fit=1200%2C675&ssl=1)
Co-occurrence Matrices Explained: How To Use Them In NLP, Computer Vision & Recommendation Systems [6 Tools]
What are Co-occurrence Matrices? Co-occurrence matrices serve as a fundamental tool across various disciplines, unveiling intricate statistical relationships hidden within data. Whether in natural...
10 Regression Metrics For Machine Learning & Practical How To Guide
What are Evaluation Metrics for Regression Models? Regression analysis is a fundamental tool in statistics and machine learning used to model the relationship between a dependent variable and one or...
![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,...
Top 9 Performance Metrics In Machine Learning & How To Use Them
Why Do We Need Performance Metrics In Machine Learning? In machine learning, the ultimate goal is to develop models that can accurately generalize to unseen data and make reliable predictions or...
