Chevron Left
Prediction Models with Sports Data(으)로 돌아가기

미시건 대학교의 Prediction Models with Sports Data 학습자 리뷰 및 피드백

4.5
별점
15개의 평가
2개의 리뷰

강좌 소개

In this course the learner will be shown how to generate forecasts of game results in professional sports using Python. The main emphasis of the course is on teaching the method of logistic regression as a way of modeling game results, using data on team expenditures. The learner is taken through the process of modeling past results, and then using the model to forecast the outcome games not yet played. The course will show the learner how to evaluate the reliability of a model using data on betting odds. The analysis is applied first to the English Premier League, then the NBA and NHL. The course also provides an overview of the relationship between data analytics and gambling, its history and the social issues that arise in relation to sports betting, including the personal risks....
필터링 기준:

Prediction Models with Sports Data의 2개 리뷰 중 1~2

교육 기관: VALAY S

2022년 7월 18일

T​his course covers basics of modeling in form of logistic regression.

T​he course is worth for those who want hands-on experience/beginning in pandas/python data science coding and those who are already familiar with mathematics & statistics of regression

교육 기관: Надежда В

2022년 2월 15일

Excellent course