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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-with-python-from-styrish-ai/
课程评论：没有评论
课程名称：机器学习与Python（来自Styrish AI） 课程概述：本课程将简要介绍机器学习及其基本概念，包括监督学习与无监督学习的区别等主题。随后，您将深入学习分类技术，涵盖多种分类算法，例如K-近邻算法（KNN）、决策树、逻辑回归和支持向量机（SVM）。此外，您还将学习回归技术的重要性与不同类型，包括简单线性回归和多元线性回归，以及它们在预测中的应用。 课程还将介绍k均值聚类，这是一种广泛使用的无监督学习算法。每节课后附有实验练习，帮助您巩固通过视频课程所获得的信息。建议您积极参与这些实验，以更好地理解课程内容。这些练习材料可下载，并包含一个可在Jupyter notebooks或Google Colab中导入的笔记本文件，以及一个Python文件。 每个主题都有测验，帮助您评估在特定主题上所达到的专业水平。参加本课程将为您开启人工智能世界的新旅程，人工智能是发展最快的技术之一，毫无疑问，它将是人类未来的基石。
This course will begin with a brief introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning and more.You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, Logistic Regression and Support Vector Machines(SVM). You'll also learn about the importance and different types of regression techniques, like simple and multiple linear regression, and how those are helpful to make the predictions. Also, you would learn k-means clustering, a widely used unsupervised learning algorithm.The lab exercises attached to each lecture will help you to digest the information you received via video lessons. To practice the lab exercises is highly recommendable to completely fit the topic into your mind. These exercise materials are downloadable and comprise a notebook file which you can import in Jupyter notebooks or Google Colab, and a python file.A quiz associated to each topic will help you to assess yourself about the level of expertise you achieved on specific topic while pursuing this course. This course will definitely help you to start your new journey into the world of artificial intelligence, which is one of the fastest-growing technologies and undoubtedly a cornerstone of humanity's future.
