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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-9-days-beginner-to-advance-using-python/
课程评论：没有评论
**课程名称：** 9天零基础到精通：Python机器学习实战 **课程概述：** 本课程将带你深入了解机器学习的核心概念，并通过丰富的现实世界案例，让你轻松掌握机器学习的不同类型。课程从Python的NumPy库入手，详细讲解多维数组的创建与操作、数据访问技巧，并对比NumPy数组与Python列表在机器学习中的优势。 随后，课程将转向Pandas库，学习如何处理各种数据集。你将熟悉Series、DataFrame和Panel等Pandas数据结构，并掌握DataFrame的数据存储、操作、缺失值处理、数据标准化以及独热编码等关键技术。 接着，课程将通过Matplotlib库进行数据可视化，发掘数据中隐藏的洞察。 最后，课程将引导你动手完成机器学习项目，包括未来预测和预测性分析。你还将学习如何将训练好的模型部署到网页上，实现模型的广泛应用，而无需暴露底层代码。 **课程适合人群：** * 对机器学习感兴趣的初学者 * 希望系统学习Python机器学习库的开发者 * 希望掌握数据分析和模型部署技能的学习者
In this course I am going to describe what is exactly Machine Learning, I will explain different types of Machine Learning with real world examples so you understands the concepts easily. Then I start with NumPy which we use to make arrays in python and that too with different dimensions of array. we together apply multiple operations on arrays, try to access desired information/data from the array and then multiple operations on array. Also we then try to figure out how NumPy array is better than Python list in case of machine Learning.After that we start working on Pandas library of Python to start working on different datasets. we understand types of pandas data type like series, DataFrame and panels and we store our data in data frames and apply different operations on DataFrame. We will try to handle missing values, data normalization, One hot encoding and much more.Then we start doing data visualization using Matplotlib library of Python which is very interesting, and by using it we are able to gather hidden insights of datasets.Then we start working on different project of Machine Learning for future prediction and concepts of forecasting.And at the end we will try to deploy our model on a webpage so anyone can use that ML model by abstracting the code.
