Dataconomy

MARCH 17, 2025

Unsupervised models Unsupervised models typically use traditional statistical methods such as logistic regression, time series analysis, and decision trees. These methods analyze data without pre-labeled outcomes, focusing on discovering patterns and relationships.

Decision Trees 91

Decision Trees Predictive Analytics Data Preparation Machine Learning 91

Ocean Protocol

NOVEMBER 28, 2024

2nd Place: Yuichiro “Firepig” [Japan] Firepig created a three-step model that used decision trees, linear regression, and random forests to predict tire strategies, laps per stint, and average lap times. Firepig refined predictions using detailed feature engineering and cross-validation.

Cross Validation 85

Cross Validation Decision Trees Data Scientist Data Science 85

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

FEBRUARY 4, 2024

The platform employs an intuitive visual language, Alteryx Designer, streamlining data preparation and analysis. With Alteryx Designer, users can effortlessly input, manipulate, and output data without delving into intricate coding, or with minimal code at most. What is Alteryx Designer?

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

Towards AI

JULY 19, 2023

(Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. Data Preparation Photo by Bonnie Kittle […]

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40

Pickl AI

NOVEMBER 18, 2024

Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. For example, linear regression is typically used to predict continuous variables, while decision trees are great for classification and regression tasks.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

OCTOBER 15, 2024

They identify patterns in existing data and use them to predict unknown events. Techniques like linear regression, time series analysis, and decision trees are examples of predictive models. Start by collecting data relevant to your problem, ensuring it’s diverse and representative.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52