学习笔记之Supervised Learning with scikit-learn | DataCamp

本课程将教你如何使用Python进行监督学习,这是机器学习的重要组成部分。你将学会构建预测模型,调整参数,并评估模型在未知数据上的表现。课程采用真实世界的数据集,使用scikit-learn这一流行且用户友好的Python机器学习库。

Supervised Learning with scikit-learn | DataCamp

  • https://www.datacamp.com/courses/supervised-learning-with-scikit-learn
    • At the end of day, the value of Data Scientists rests on their ability to describe the world and to make predictions. Machine Learning is the field of teaching machines and computers to learn from existing data to make predictions on new data - will a given tumor be benign or malignant? Which of your customers will take their business elsewhere? Is a particular email spam or not? In this course, you'll learn how to use Python to perform supervised learning, an essential component of Machine Learning. You'll learn how to build predictive models, how to tune their parameters and how to tell how well they will perform on unseen data, all the while using real world datasets. You'll do so using scikit-learn, one of the most popular and user-friendly machine learning libraries for Python.
  • https://github.com/haoran119/data-science/tree/master/src/DataCamp/Supervised%20Learning%20with%20scikit-learn

  • Which of them is a supervised classification problem?
    • Using labeled financial data to predict whether the value of a stock will go up or go down next week.
    • Using labeled housing price data to predict the price of a new house based on various features.
    • Using unlabeled data to cluster the students of an online education company into different categories based on their learning styles.
    • Using labeled financial data to predict what the value of a stock will be next week.

 

转载于:https://www.cnblogs.com/pegasus923/p/10102090.html

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值