Data Preparation, Hypothesis Testing and Supervised Learning

Must-Have Skills for a Machine Learning Engineer

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. These techniques span different types of learning and provide powerful tools to solve complex real-world problems.

Machine Learning

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

MAY 15, 2023

In Inferential Statistics, you can learn P-Value , T-Value , Hypothesis Testing , and A/B Testing , which will help you to understand your data in the form of mathematics. In Descriptive Statistics, you need to focus on topics like Mean , Median , Mode, and Standard Deviation.

Data Science

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Data Science Current

Must-Have Skills for a Machine Learning Engineer

Roadmap to Learn Data Science for Beginners and Freshers in 2023

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