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...
The Natural Language Processing (NLP) Blog
Topic: Tutorial
Dimensionality Reduction Explained, Top 5 Techniques & How To Tutorial In Python
What is dimensionality reduction in machine learning? Dimensionality reduction is a technique used in machine learning and data analysis to reduce the number of features or variables in a dataset...
One-shot Learning Explained, How It Works & How To Tutorial In Python
What is one-shot learning? One-shot learning is a machine learning paradigm that trains models to recognize new objects or patterns based on a single example or a minimal number of examples....
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...
![Practical Guide To Grid Search [How To In Python For SVM & Logistic Regression]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/grid-search.jpg?fit=960%2C540&ssl=1)
Practical Guide To Grid Search [How To In Python For SVM & Logistic Regression]
What is grid search? Grid search is a hyperparameter tuning technique commonly used in machine learning to find a given model's best combination of hyperparameters. Hyperparameters are parameters...
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...
![Deep Dive into Active Learning in Machine Learning [How To In Python & PyTorch]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/active-learning-try-fail.jpg?fit=1200%2C675&ssl=1)
Deep Dive into Active Learning in Machine Learning [How To In Python & PyTorch]
What is active learning in machine learning? Active learning is a machine learning technique that involves iteratively selecting and labelling the most informative examples from an unlabeled dataset...
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...
![Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/zero-shot-classification.jpg?fit=1200%2C675&ssl=1)
Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]
What is zero-shot classification? Zero-shot classification is a machine learning approach in which a model can classify data into multiple classes without any specific training examples for those...
![How To Apply Feature Scaling In Machine Learning [Top Methods & Tutorials In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/07/min-max-feature-scaling.jpg?fit=1200%2C675&ssl=1)
How To Apply Feature Scaling In Machine Learning [Top Methods & Tutorials In Python]
What is feature scaling in machine learning? Feature scaling is a preprocessing technique used in machine learning and data analysis to bring all the input features to a similar scale. It is...
K-Fold Cross-validation Complete Guide — How To Tutorial In Machine Learning & Deep Learning
What is k-fold cross-validation? K-fold cross-validation is a popular technique used to evaluate the performance of machine learning models. It is advantageous when you have limited data and want to...
Understanding & Implementing The Continuous Bag-of-Words (CBOW) Model
Introduction to word embeddings Word embeddings have become a cornerstone of Natural Language Processing (NLP), transforming how machines process and understand human language. These vector...
Top 6 Name Matching Algorithm, How To Scale Your Solution & Tutorial In Python
What is fuzzy name matching? A fuzzy name matching algorithm, or approximate name matching, is a technique used to compare and match names with slight differences, variations, or errors. It is...
Graph Neural Network Explained & How To Tutorial In Python With PyTorch
Graph Neural Network (GNN) is revolutionizing the field of machine learning by enabling effective modelling and analysis of structured data. Originally designed for graph-based data, GNNs have found...
