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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-with-polars/
课程评论：没有评论
课程名称：使用 Polars 进行机器学习 课程概述：机器学习（ML）和人工智能（AI）是当今创新的关键驱动力。理解这些模型的工作方式将帮助你有效应用 ML 技术。在本课程中，专家讲师 Joram Mutenge 将教你如何掌握机器学习的基本要素，并利用 Python 和高性能的 Polars 库进行高级数据处理。你将构建一个端到端的机器学习应用程序，以预测笔记本电脑的价格。通过构建这个 ML 应用程序，你将获得数据探索、数据处理、模型创建、模型评估、模型调优和模型部署（使用 MLFlow）的实践经验。 讲师背景：Joram 拥有伊利诺伊大学厄本那-香槟分校的数据科学硕士学位，目前在一家制造公司从事数据工作，构建需求预测模型。他在构建和部署机器学习模型方面拥有多年的经验。在本课程中，他将分享他在这一路径上所学习到的经验。 课程建议：本课程的各个模块是相互连接的，建议按照模块的呈现顺序进行学习，这将帮助你更好地理解材料。为了进一步巩固理解，建议在计算机上输入并运行代码，而不是被动观看。最后，将所学知识应用到你自己的数据集上，以加深理解。
Machine learning (ML) and AI are the key drivers of innovation today. Understanding how these models work can help you apply ML techniques effectively.In this course, expert instructor Joram Mutenge shows you how to master machine learning essentials by leveraging Python and the high-performance Polars library for advanced data manipulation.You will build an end-to-end machine learning application to predict laptop prices. Building this ML application will help you gain hands-on experience in data exploration, data processing, model creation, model evaluation, model tuning, and model deployment with MLFlow.Learn from a Data Science PractionerJoram has a master's degree in Data Science from the University of Illinois Urbana-Champaign, and currently works in data at a manufacturing company building demand forecasting models. He has years of experience building and deploying machine learning models. In this course, he shares the lessons he has learned along the way.Making the most of this courseThe modules in this course build on top of each other. Learn by following the order in which these modules are presented. This will help you understand the material better. To further cement the understanding, type out the code and run it on your computer instead of passively watching. Finally, apply the knowledge learned to your own dataset.
