강의
Python으로 통계 면접 문제 연습하기
고급기술 수준
업데이트됨 2022. 6.
PythonProbability & Statistics4시간15 동영상46 연습 문제3,700 XP16,518성취 증명서
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선수 조건
Hypothesis Testing in PythonSupervised Learning with scikit-learn1
Probability and Sampling Distributions
This chapter kicks the course off by reviewing conditional probabilities, Bayes' theorem, and central limit theorem. Along the way, you will learn how to handle questions that work with commonly referenced probability distributions.
2
Exploratory Data Analysis
In this chapter, you will prepare for statistical concepts related to exploratory data analysis. The topics include descriptive statistics, dealing with categorical variables, and relationships between variables. The exercises will prepare you for an analytical assessment or stats-based coding question.
3
Statistical Experiments and Significance Testing
Prepare to dive deeper into crucial concepts regarding experiments and testing by reviewing confidence intervals, hypothesis testing, multiple tests, and the role that power and sample size play. We'll also discuss types of errors, and what they mean in practice.
4
Regression and Classification
Wrapping up, we'll address concepts related closely to regression and classification models. The chapter begins by reviewing fundamental machine learning algorithms and quickly ramps up to model evaluation, dealing with special cases, and the bias-variance tradeoff.
Python으로 통계 면접 문제 연습하기
강의 완료
19백만 명 이상의 학습자와 함께 Python으로 통계 면접 문제 연습하기을(를) 시작하세요!
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