Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. 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

Pickl AI

OCTOBER 15, 2024

Hypothesis Testing : Statistical Models help test hypotheses by analysing relationships between variables. These models help in hypothesis testing and determining the relationships between variables. Bayesian models and hypothesis tests (like t-tests or chi-square tests) are examples of inferential models.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

SEPTEMBER 12, 2024

Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset. Inferential Statistics: A branch of statistics that makes inferences about a population based on a sample, allowing for hypothesis testing and confidence intervals.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52