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...
The Natural Language Processing (NLP) Blog
Topic: Tutorial
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...
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...
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...
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Natural Language Search Explained [10 Powerful Tools & How To Tutorial In Python]
What is Natural Language Search? Natural language search refers to the capability of search engines and other information retrieval systems to understand and interpret human language in its natural...
![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...
Stochastic Gradient Descent (SGD) In Machine Learning Explained & How To Implement
Understanding Stochastic Gradient Descent (SGD) In Machine Learning Stochastic Gradient Descent (SGD) is a pivotal optimization algorithm widely utilized in machine learning for training models....
Multilayer Perceptron Explained And How To Train & Optimise MLPs
What is a Multilayer perceptron (MLP)? In artificial intelligence and machine learning, the Multilayer Perceptron (MLP) stands as one of the foundational architectures, wielding remarkable...
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Bayesian Network Made Simple [How It Is Used In Artificial Intelligence & Machine Learning]
What is a Bayesian Network? Bayesian network, also known as belief networks or Bayes nets, are probabilistic graphical models representing random variables and their conditional dependencies via a...
![How To Implement Speech Recognition [3 Ways & 7 Machine Learning Models]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/01/speech-recognition.jpg?fit=1200%2C675&ssl=1)
How To Implement Speech Recognition [3 Ways & 7 Machine Learning Models]
What is Speech Recognition? Speech recognition, also known as automatic speech recognition (ASR) or voice recognition, is a technology that converts spoken language into written text. The primary...
Node2Vec: Extensive Guide & How To Tutorial In Python
What is Node2Vec? Node2Vec is a popular algorithm for learning continuous representations (embeddings) of nodes in a graph. It is a technique in network representation learning, which involves...
Explainable AI Made Simple: 5 Techniques, Tools & How To Tutorials
What is Explainable AI? In today's data-driven world, artificial intelligence (AI) has revolutionised various aspects of our lives, from healthcare diagnostics to financial risk assessment. However,...
Universal Sentence Encoder Explained & How To TensorFlow Tutorial
What is a Universal Sentence Encoder? The Universal Sentence Encoder (USE) is a powerful tool in natural language processing (NLP) developed by Google. Its primary function is to transform textual...
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Semi-Supervised Machine Learning Made Simple [5 Algorithms & How To Python Tutorial]
What is Semi-Supervised Learning in Machine Learning? Semi-supervised learning is a machine learning paradigm between supervised and unsupervised learning. In this approach, the algorithm learns...
Variational Autoencoders (VAEs) Made Simple & How To TensorFlow Tutorial
What are Variational Autoencoders (VAEs)? Autoencoders are ingenious, unsupervised learning mechanisms capable of learning efficient data representations. However, traditional autoencoders often...
![t-SNE Explained: Top 6 Tools & Practical How To Get Started Guide [Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/t-sne-visual-explanation.jpg?fit=1200%2C675&ssl=1)
t-SNE Explained: Top 6 Tools & Practical How To Get Started Guide [Python]
What is t-SNE? t-SNE, or t-distributed Stochastic Neighbor Embedding, is a popular non-linear dimensionality reduction technique used primarily for visualizing high-dimensional data in a...
Prototypical Networks Explained, Compared To Other Networks & How To Tutorial In PyTorch
What is a Prototypical Network? At its core, Prototypical Networks represent a groundbreaking approach to tackling the complexities of classification problems, especially in scenarios where labelled...
