What is Batch Gradient Descent? Batch gradient descent is a fundamental optimization algorithm in machine learning and numerical optimisation tasks. It is a variation of the gradient descent...
About Neri Van Otten
Neri Van Otten is the founder of Spot Intelligence, a machine learning engineer with over 12 years of experience specialising in Natural Language Processing (NLP) and deep learning innovation. Dedicated to making your projects succeed.
Posts By Neri Van Otten
![Bias Mitigation in Machine Learning [Practical How-To Guide & 12 Strategies]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/05/techniques-bias-detection.jpg?fit=1440%2C810&ssl=1)
Bias Mitigation in Machine Learning [Practical How-To Guide & 12 Strategies]
In machine learning (ML), bias is not just a technical concern—it's a pressing ethical issue with profound implications. As AI systems become increasingly integrated into our daily lives, from...
Full-Text Search Explained, How To Implement & 6 Powerful Tools
What is Full-Text Search? Full-text search is a technique for efficiently and accurately retrieving textual data from large datasets. Unlike traditional search methods that rely on simple string...
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...
Weight Decay In Machine Learning And Deep Learning Explained & How To Tutorial
What is Weight Decay in Machine Learning? Weight decay is a pivotal technique in machine learning, serving as a cornerstone for model regularisation. As algorithms become increasingly complex and...
Cosine Annealing In Machine Learning Simplified: Understand How It Works
What is Cosine Annealing? In the vast landscape of optimisation algorithms lies a hidden gem that has been gaining increasing attention in recent years: cosine annealing. Optimisation algorithms are...
![Collaborative Filtering In Machine Learning Made Simple [6 Different Approaches]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/user-based-collaborative-filtering.jpg?fit=1200%2C675&ssl=1)
Collaborative Filtering In Machine Learning Made Simple [6 Different Approaches]
What is Collaborative Filtering? In today's digital era, where we are inundated with overwhelming information and choices, recommendation systems have become indispensable. From suggesting movies to...
Online Machine Learning Explained & How To Build A Powerful Adaptive Model
What is Online Machine Learning? Online machine learning, also known as incremental or streaming learning, is a type of machine learning in which models are updated continuously as new data becomes...
Data Drift In Machine Learning Explained: How To Detect & Mitigate It
What is Data Drift Machine Learning? In machine learning, the accuracy and effectiveness of models heavily rely on the quality and consistency of the data on which they are trained. However, in...
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...
![Co-occurrence Matrices Explained: How To Use Them In NLP, Computer Vision & Recommendation Systems [6 Tools]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/co-occurance-matrix.jpg?fit=1200%2C675&ssl=1)
Co-occurrence Matrices Explained: How To Use Them In NLP, Computer Vision & Recommendation Systems [6 Tools]
What are Co-occurrence Matrices? Co-occurrence matrices serve as a fundamental tool across various disciplines, unveiling intricate statistical relationships hidden within data. Whether in natural...
![Query Understanding In NLP Simplified & How It Works [5 Techniques]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/query-understanding.jpg?fit=1200%2C675&ssl=1)
Query Understanding In NLP Simplified & How It Works [5 Techniques]
What is Query Understanding? Understanding user queries lies at the heart of efficient communication between humans and machines in the vast digital information and interaction landscape. Query...
![Distributional Semantics Simplified & 7 Techniques [How To Understand Language]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/03/distributional-semantics.jpg?fit=1200%2C675&ssl=1)
Distributional Semantics Simplified & 7 Techniques [How To Understand Language]
What is Distributional Semantics? Understanding the meaning of words has always been a fundamental challenge in natural language processing (NLP). How do we decipher the intricate nuances of...
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...
![Natural Language Search Explained [10 Powerful Tools & How To Tutorial In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/10/Ontwerp-zonder-titel-8.jpg?fit=600%2C338&ssl=1)
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...
