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...
The Natural Language Processing (NLP) Blog
Topic: Tutorial
![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...
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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...
Few-shot Learning Explained & Step-by-step How To Python Tutorial
What is few-shot learning? Few-shot learning is a machine learning technique that aims to train models to learn new tasks or recognise new classes of objects using only a small amount of labelled...
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...
L1 And L2 Regularization Explained, When To Use Them & Practical How To Examples
L1 and L2 regularization are techniques commonly used in machine learning and statistical modelling to prevent overfitting and improve the generalization ability of a model. They are regularization...
Hyperparameter Tuning In Machine Learning And Deep Learning: Top 6 Ways & How To Tutorial
What is hyperparameter tuning in machine learning? Hyperparameter tuning is critical to machine learning and deep learning model development. Machine learning algorithms typically have specific...
CountVectorizer Tutorial: How To Easily Turn Text Into Features For Any NLP Task
What is CountVectorizer in NLP? CountVectorizer is a text preprocessing technique commonly used in natural language processing (NLP) tasks for converting a collection of text documents into a...
F1 Score The Ultimate Guide: Formulas, Explanations, Examples, Advantages, Disadvantages, Alternatives & Python Code
The F1 score formula The F1 score is a metric commonly used to evaluate the performance of binary classification models. It is a measure of a model's accuracy, and it takes into account both...
Latent Dirichlet Allocation (LDA) Made Easy And Top 3 Ways To Implement In Python
Latent Dirichlet Allocation explained Latent Dirichlet Allocation (LDA) is a statistical model used for topic modelling in natural language processing. It is a generative probabilistic model that...
Fine-tuning GPT-3: How To Tutorial In Python With Hugging Face
What is GPT-3? GPT-3 (Generative Pre-trained Transformer 3) is a state-of-the-art language model developed by OpenAI, a leading artificial intelligence research organization. GPT-3 is a deep neural...
![How To Guide To Bias-Variance Trade-Off [2 Examples In Python: Polynomial Regression & SVM]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/04/bias-varince-trade-off.jpg?fit=960%2C540&ssl=1)
How To Guide To Bias-Variance Trade-Off [2 Examples In Python: Polynomial Regression & SVM]
What are bias, variance and the bias-variance trade-off? The bias-variance trade-off is a fundamental concept in supervised machine learning that refers to the trade-off between the error due to...
N-grams Made Simple & How To Implement In Python (NLTK)
In natural language processing, n-grams are a contiguous sequence of n items from a given sample of text or speech. These items can be characters, words, or other units of text, and they are used to...
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How To Implement Natural Language Processing (NLP) Feature Engineering In Python [8 Techniques]
Natural Language Processing (NLP) feature engineering involves transforming raw textual data into numerical features that can be input into machine learning models. Feature engineering is a crucial...
