描述

Sabrina Moore

This course will teach you how to leverage the power of Python and artificial intelligence to create and test hypothesis. We'll start for the ground up, learning some basic Python for data science before diving into some of its richer applications to test our created hypothesis. We'll learn some of the most important libraries for exploratory data analysis (EDA) and machine learning such as Numpy, Pandas, and Sci-kit learn. After learning some of the theory (and math) behind linear regression, we'll go through and full pipeline of reading data, cleaning it, and applying a regression model to estimate the progression of diabetes. By the end of the course, you'll apply a classification model to predict the presence/absence of heart disease from a patient's health data.阅读更多.

此资源由附属合作伙伴提供。 如果您支付培训费用，我们可能会赚取佣金来支持该网站。

按照数据工作岗位排列职业相关性

Introduction to Data Science and scikit-learn in Python 中涵盖的技术和工具与 数据科学家 招聘广告中的要求最为相似。