Dataconomy

MARCH 17, 2025

By analyzing data from IoT devices, organizations can perform maintenance tasks proactively, reducing downtime and operational costs. Data preparation Data preparation is a crucial step that includes data cleaning, transforming, and structuring historical data for analysis.

Decision Trees 91

Decision Trees Predictive Analytics Data Preparation Machine Learning 91

Towards AI

AUGUST 16, 2023

Data description: This step includes the following tasks: describe the dataset, including the input features and target feature(s); include summary statistics of the data and counts of any discrete or categorical features, including the target feature. Training: This step includes building the model, which may include cross-validation.

AI 96

AI AI Machine Learning Machine Learning 96

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.

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

OCTOBER 15, 2024

Summary: Statistical Modeling is essential for Data Analysis, helping organisations predict outcomes and understand relationships between variables. Introduction Statistical Modeling is crucial for analysing data, identifying patterns, and making informed decisions. Data preparation also involves feature engineering.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Data Transformation Transforming data prepares it for Machine Learning models.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78