What is Linear Regression in Machine Learning? Linear regression is one of the fundamental techniques in machine learning and statistics used to understand the relationship between one or more...
The Natural Language Processing (NLP) Blog
Topic: Machine Learning Models
![Wavelet Transform Made Simple [Foundation, Applications, Advantages]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/09/wave-vs-wavelets.jpg?fit=1200%2C675&ssl=1)
Wavelet Transform Made Simple [Foundation, Applications, Advantages]
Introduction to Wavelet Transform What is Signal Processing? Signal processing is critical in various fields, from telecommunications to medical diagnostics and multimedia applications. It involves...
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...
![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,...
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...
Support Vector Machines (SVM) In Machine Learning Made Simple & How To Tutorial
What are Support Vector Machines? Machine learning algorithms transform raw data into actionable insights. Among these algorithms, Support Vector Machines (SVMs) stand out as a core algorithm for...
What Are Gaussian Mixture Models (GMMs)? & How To Python Tutorial With Scikit-Learn
What are Gaussian Mixture Models (GMMs)? Gaussian Mixture Models (GMM) are probabilistic models representing a probability distribution as a mixture of multiple Gaussian (normal) distributions. It...
DBSCAN Made Simple & How To Python Tutorial With Scikit-Learn
What is DBSCAN? DBSCAN stands for "Density-Based Spatial Clustering of Applications with Noise." It is a popular clustering algorithm used in machine learning and data mining to group data points...
Latent Semantic Analysis: A Complete Guide With Alternatives & Python Tutorial
What is Latent Semantic Analysis (LSA)? Latent Semantic Analysis (LSA) is used in natural language processing and information retrieval to analyze word relationships in a large text corpus. It is a...
KMeans Explained, Practical Guide To Data Clustering & How To In Python
What is KMeans? KMeans is a popular clustering algorithm used in machine learning and data analysis. It's used to partition a dataset into distinct, non-overlapping clusters. The goal of KMeans is...
K-Nearest Neighbours Explained, Practical Guide & How To Tutorial In Python
What is K-nearest neighbours? K-Nearest Neighbours (KNN) is a simple and widely used classification and regression algorithm in machine learning. It falls under the category of supervised learning...
AdaBoost: Practical Introduction With How To Python Tutorial For Classification & Regression
What is AdaBoost? AdaBoost, short for Adaptive Boosting, is a machine learning algorithm that belongs to the ensemble learning techniques. Ensemble learning involves combining the predictions of...
Gradient Boosting Explained & How To Tutorials In Python With XGBoost
What is gradient boosting? Gradient Boosting is a powerful machine learning technique for classification and regression tasks. It's an ensemble learning method that combines the predictive abilities...
Softmax Regression Explained And How To Tutorial In Python & PyTorch
What is softmax regression? Softmax regression, or multinomial logistic regression or maximum entropy classifier, is a machine learning technique used for classification problems where the goal is...
![Multi-class Classification Explained With 3 How To Python Tutorials [Scikit-Learn, PyTorch & Keras]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/multi-class-classification.jpg?fit=1200%2C675&ssl=1)
Multi-class Classification Explained With 3 How To Python Tutorials [Scikit-Learn, PyTorch & Keras]
What is multi-class classification in machine learning? Multi-class classification is a machine learning task that aims to assign input data points to one of several predefined classes or...
Top 6 Most Powerful Ensemble Learning Techniques Explained & Algorithms That Implement Them
What is ensemble learning in machine learning? Ensemble learning is a machine learning technique that combines the predictions of multiple individual models to improve a machine learning algorithm's...
Comparative Guide: Top 7 Outlier Detection Algorithms & How To Tutorials In Python
Outlier detection in machine learning Outlier detection is a task in machine learning and data analysis involving identifying points that deviate significantly from the rest of the data. These data...
How To Implement Logistic Regression Text Classification In Python With Scikit-learn and PyTorch
Text classification is a fundamental problem in natural language processing (NLP) that involves categorising text data into predefined classes or categories. It can be used in many real-world...
