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所在平台: Udemy |
课程主页: https://www.udemy.com/course/supervisedlearning/
课程评论：没有评论
课程名称：分类模型：Python中的有监督机器学习 课程概述：人工智能和机器学习日益渗透到我们的日常生活中，为各行各业带来更高的效率和智能。有监督机器学习是其背后的核心方法之一。该方法通过使用算法分析和学习过去的观察数据，从而能够预测未来事件。本课程将介绍有监督机器学习中一种重要的建模方法——分类。您将学习如何使用Python的Scikit learn（sklearn）库实现有监督分类机器学习模型。 课程内容包括流行和广泛使用的分类技术，例如：支持向量机、朴素贝叶斯、决策树、随机森林、K-近邻、神经网络和逻辑回归。您将学习如何训练预测模型来分类类别结果，并使用性能指标评估不同模型。课程通过多个示例引导您编码，并使用真实数据集进行练习。 课程结束时，您将能够构建机器学习模型，根据自身数据进行预测。课程中包含的完整Python程序和数据集也可供下载。本课程设计旨在有效利用您的时间，帮助您更好地学习。 职业发展：根据就业网站Indeed的数据显示，机器学习工程师被评选为美国最佳职位之一，增长率达344%，年薪中位数为146,085美元。整体来看，计算机和信息技术职位正在蓬勃发展，预计从2019年到2029年就业率将增长11%。
Artificial intelligence and machine learning are touching our everyday lives in more-and-more ways. There's an endless supply of industries and applications that machine learning can make more efficient and intelligent. Supervised machine learning is the underlying method behind a large part of this. Supervised learning involves using some algorithm to analyze and learn from past observations, enabling you to predict future events. This course introduces you to one of the prominent modelling families of supervised Machine Learning called Classification. This course will teach you to implement supervised classification machine learning models in Python using the Scikit learn (sklearn) library. You will become familiar with the most successful and widely used classification techniques, such as:Support Vector Machines.Naive BayesDecision TreeRandom ForestK-Nearest NeighborsNeural NetworksLogistic RegressionYou will learn to train predictive models to classify categorical outcomes and use performance metrics to evaluate different models. The complete course is built on several examples where you will learn to code with real datasets. By the end of this course, you will be able to build machine learning models to make predictions using your data. The complete Python programs and datasets included in the class are also available for download. This course is designed most straightforwardly to utilize your time wisely. Get ready to do more learning than your machine!Happy Learning.Career Growth:Employment website Indeed has listed machine learning engineers as #1 among The Best Jobs in the U.S., citing a 344% growth rate and a median salary of $146,085 per year. Overall, computer and information technology jobs are booming, with employment projected to grow 11% from 2019 to 2029.
