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...
The Natural Language Processing (NLP) Blog
Topic: Data Science
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...
Understanding Dropout in Neural Network: Enhancing Robustness and Generalization
What is dropout in neural networks? Dropout is a regularization technique used in a neural network to prevent overfitting and enhance model generalization. Overfitting occurs when a neural network...
![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...
![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...
Unveiling the Hidden Peril: Understanding Data Leakage in Machine Learning
Welcome to our blog post, where we delve into a critical aspect of machine learning that often goes unnoticed but can significantly impact the reliability of our models - data leakage. As...
![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...
Skip-gram Models Explained & How To Create Embeddings In Word2Vec
What is skip-gram? Skip-gram is a popular algorithm used in natural language processing (NLP), specifically in word embedding techniques. It is a method for learning word representations in a 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...
How To Combine Numerical & Text Features: 10 Ways In Machine Learning And Deep Learning
Why Combine Numerical Features And Text Features? Combining numerical and text features in machine learning models has become increasingly important in various applications, particularly natural...
