What are ROC and AUC Curves in Machine Learning? The ROC Curve The ROC (Receiver Operating Characteristic) curve is a graphical representation used to evaluate the performance of binary...
The Natural Language Processing (NLP) Blog
Topic: Optimisation
Batch Gradient Descent In Machine Learning Made Simple & How To Tutorial In Python
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...
![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...
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...
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...
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...
![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...
Learning Rate In Machine Learning And Deep Learning Made Simple
Machine learning algorithms are at the core of many modern technological advancements, powering everything from recommendation systems to autonomous vehicles. Optimisation is central to the...
The Cold-Start Problem In Machine Learning Explained & 6 Mitigating Strategies
What is the Cold-Start Problem in Machine Learning? The cold-start problem refers to a common challenge encountered in machine learning systems, particularly in recommendation systems, where the...
![Exploding Gradient Explained: How To Detect & Overcome It [6 Best Practices]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/12/exploding-gradient.jpg?fit=1200%2C675&ssl=1)
Exploding Gradient Explained: How To Detect & Overcome It [6 Best Practices]
What is the Exploding Gradient Problem? Neural networks optimize their parameters using gradient-based optimization algorithms like gradient descent. Gradients represent the slope of the loss...
Gradient Clipping Explained & Practical How To Guide In Python
What is Gradient Clipping in Machine Learning? Gradient clipping is used in deep learning models to prevent the exploding gradient problem during training. During the training process of neural...
![How to manage Large Language Models (LLM) — Orchestration Made Simple [5 Frameworks]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/11/llm-orchestration.jpg?fit=1200%2C675&ssl=1)
How to manage Large Language Models (LLM) — Orchestration Made Simple [5 Frameworks]
What is LLM Orchestration? LLM orchestration is the process of managing and controlling large language models (LLMs) in a way that optimizes their performance and effectiveness. This includes tasks...
![Feature Extraction: Extensive Guide & 3 How To Tutorials [Python, CNN, BERT]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/11/feature-extraction-cats-dogs-example.jpg?fit=1200%2C675&ssl=1)
Feature Extraction: Extensive Guide & 3 How To Tutorials [Python, CNN, BERT]
What is Feature Extraction in Machine Learning? Feature extraction is a fundamental concept in data analysis and machine learning, serving as a crucial step in the process of transforming raw data...
