Data Science Dojo

AUGUST 19, 2024

.” Unsupervised learning: In this type of learning, the model is trained on unlabeled data, and it must discover patterns or structures within the data itself. This is used for tasks like clustering, dimensionality reduction, and anomaly detection.

AI 363

AI AI Machine Learning Machine Learning 363

Pickl AI

AUGUST 29, 2023

Model Selection: You need to choose an appropriate statistical model or technique that is based on the nature of the data and research question. This could be linear regression, logistic regression, clustering , time series analysis , etc. This may involve finding values that best represent to observed data.

Data Scientist 52

Data Scientist Clustering Data Analysis Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Unsupervised Learning Unsupervised learning involves training models on data without labels, where the system tries to find hidden patterns or structures. This type of learning is used when labelled data is scarce or unavailable. Incorporating automated testing ensures the model remains robust even as the codebase evolves.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

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. There is no licensing cost for Scikit-learn, you can create and use different ML models with Scikit-learn for free.

Machine Learning 59

Machine Learning Machine Learning ML ML 59