Remove Cross Validation Remove Hypothesis Testing Remove Natural Language Processing
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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Key Deep Learning models include: Convolutional Neural Networks (CNNs) CNNs are designed to process structured grid data, such as images.

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

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.