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...
The Natural Language Processing (NLP) Blog
Topic: Optimisation
![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...
![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...
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...
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...
Endogenous vs Exogenous Variables Explained With Examples & Why It’s Important For Machine Learning
Endogenous and exogenous variables are two important concepts. In machine learning, endogenous variables are the variables that are directly influenced by other variables within the system being...
![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...
Data Quality In Machine Learning – Explained, Issues, How To Fix Them & Python Tools
What is data quality in machine learning? Data quality is a critical aspect of machine learning (ML). The quality of the data used to train a ML model directly impacts the accuracy and effectiveness...
