Courses
Pythonで統計面接問題を練習しよう
高度なスキルレベル
更新 2022/06無料でコースを始める
含まれるものプレミアム or チーム
PythonProbability & Statistics4時間15 videos46 Exercises3,700 XP16,223達成証明書
数千社の学習者に愛用されています
2人以上をトレーニングしますか?
DataCamp for Businessを試すコースの説明
前提条件
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.
Pythonで統計面接問題を練習しよう
コース完了