Pickl AI

NOVEMBER 28, 2024

Key techniques in unsupervised learning include: Clustering (K-means) K-means is a clustering algorithm that groups data points into clusters based on their similarities. Unit testing ensures individual components of the model work as expected, while integration testing validates how those components function together.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Data Science Dojo

AUGUST 24, 2023

MLOps practices include cross-validation, training pipeline management, and continuous integration to automatically test and validate model updates. Examples include: Cross-validation techniques for better model evaluation. Managing training pipelines and workflows for a more efficient and streamlined process.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Pickl AI

OCTOBER 15, 2024

Applications : Stock price prediction and financial forecasting Analysing sales trends over time Demand forecasting in supply chain management Clustering Models Clustering is an unsupervised learning technique used to group similar data points together. Popular clustering algorithms include k-means and hierarchical clustering.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

SEPTEMBER 12, 2024

Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities. Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

JUNE 28, 2023

This extensive repertoire includes classification, regression, clustering, natural language processing, and anomaly detection. The compare_models() function trains all available models in the PyCaret library and evaluates their performance using cross-validation, providing a simple way to select the best-performing model.

Machine Learning 52

Machine Learning Machine Learning Data Preparation Data Science 52

DataRobot Blog

DECEMBER 20, 2022

For example, the model produced a RMSLE (Root Mean Squared Logarithmic Error) Cross Validation of 0.0825 and a MAPE (Mean Absolute Percentage Error) Cross Validation of 6.215. This would entail a roughly +/-€24,520 price difference on average, compared to the true price, using MAE (Mean Absolute Error) Cross Validation.

AI 59

AI AI Cross Validation Machine Learning 59

DagsHub

APRIL 21, 2024

It offers implementations of various machine learning algorithms, including linear and logistic regression , decision trees , random forests , support vector machines , clustering algorithms , and more. You must evaluate the level of support and documentation provided by the tool vendors or the open-source community.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

DECEMBER 10, 2024

Projecting data into two or three dimensions reveals hidden structures and clusters, particularly in large, unstructured datasets. TF-IDF (Term Frequency-Inverse Document Frequency) TF-IDF builds on BoW by emphasising rare and informative words while minimising the weight of common ones.

Machine Learning 52

Machine Learning Machine Learning Algorithm Deep Learning 52

The MLOps Blog

JUNE 6, 2023

Perform cross-validation using StratifiedKFold. We perform cross-validation using the StratifiedKFold method, which splits the training data into K folds, maintaining the proportion of classes in each fold. The model is trained K times, using K-1 folds for training and one fold for validation.

ML 52

ML ML Cross Validation Machine Learning 52

Dataconomy

MARCH 27, 2025

Its user-friendly nature and extensive documentation make it accessible to newcomers while still holding great promise for seasoned practitioners. Key aspects include a focus on usability, code quality, and comprehensive documentation, ensuring that users can apply the library effectively.

Machine Learning 91

Machine Learning Machine Learning Cross Validation Clustering 91