Predict Career Longevity for NBA Rookies using Scikit-learn

提供方
Coursera Project Network
在此指导项目中,您将:

Visualize data for insights

Create binary classification model using logistic regression

Clock1 hour
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培养的技能

Data SciencePython Programming

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Load the dataset that we will work on

  2. Find insights in our data

  3. Do features selection using correlation heat map

  4. Do binary classification using logistic regression

  5. Adjust the discrimination threshold to increase or decrease the sensitivity to false positives or to other application factors

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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