Data Science Dojo

FEBRUARY 14, 2024

Normalization A feature scaling technique is often applied as part of data preparation for machine learning. The goal of normalization is to change the value of numeric columns in the dataset to use a common scale, without distorting differences in the range of values or losing any information.

K-nearest Neighbors 243

K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 243

Dataconomy

MARCH 28, 2025

Specific types of machine learning algorithms Among the several algorithms available, some notable types include: Support vector machine (SVM): Ideal for binary classification tasks. Understanding data preparation Successful implementation of machine learning algorithms hinges on thorough data preparation.

Machine Learning 91

Machine Learning Machine Learning Algorithm K-nearest Neighbors 91

How to Learn Machine Learning

MARCH 25, 2025

It groups similar data points or identifies outliers without prior guidance. Type of Data Used in Each Approach Supervised learning depends on data that has been organized and labeled. This data preparation process ensures that every example in the dataset has an input and a known output.

Supervised Learning 59

Supervised Learning Machine Learning Machine Learning Algorithm 59

Pickl AI

JULY 12, 2024

Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes. This section explores the essential steps in preparing data for AI applications, emphasising data quality’s active role in achieving successful AI models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

JULY 1, 2024

Data Preparation for Demand Forecasting High-quality data is the cornerstone of effective demand forecasting. Just like building a house requires a strong foundation, building a reliable forecast requires clean and well-organized data. They are particularly effective when dealing with high-dimensional data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

phData

AUGUST 24, 2023

Various machine learning algorithms can be used for credit scoring and decisioning, including logistic regression, decision trees, random forests, support vector machines, and neural networks. Data Preparation The first step in the process is data collection and preparation.

ML 52

ML ML Machine Learning Machine Learning 52

PyImageSearch

SEPTEMBER 16, 2024

Supervised Learning These methods require labeled data to train the model. The model learns to distinguish between normal and abnormal data points. For example, in fraud detection, SVM (support vector machine) can classify transactions as fraudulent or non-fraudulent based on historically labeled data.

Clustering 57

Clustering Algorithm Machine Learning Machine Learning 57