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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-regression-and-feedforward-networks-2024/
课程评论：没有评论
《Master Regression and Feedforward Networks [2025]》是一门旨在帮助学习者精通回归和前馈网络的课程。该课程涵盖了从基础线性回归到高级多元多项式回归，特别是 eXtreme Gradient Boosting (XGBoost) 回归等多种回归技术。 **核心学习内容：** * **回归与预测精通：** 理论与实践相结合，深入理解回归分析和预测。 * **模型构建与技术：** 学习创建机器学习自动模型，掌握特征选择。 * **高级回归模型：** 深入研究决策树、随机森林、XGBoost 以及投票回归模型。 * **网络结构：** 学习前馈多层神经网络和高级回归模型结构。 * **模型评估：** 掌握残差分析，评估模型的拟合优度。 * **工具与库：** 熟练使用 Statsmodels、Scikit-learn、Matplotlib、Seaborn、Pandas 以及 Python。 * **云计算与环境：** 学习使用 Anaconda Cloud Notebook 进行云端计算，了解 Conda 包管理系统。 **适用人群：** * 希望精通回归和预测的学习者。 * 对机器学习自动模型创建感兴趣的人。 * 希望提升数据科学和机器学习能力及效率的专业人士。 **课程优势：** * 提供超过10小时的视频教程，配有手动编辑的英文字幕。 * 课程内容全面，从理论到实践，涵盖了当前最重要和最常用的建模、预测和人工智能工具。 * 提供免费软件，并包含云端计算和 Windows 10/11 的安装设置视频。 * 需要一定的 Python 和 Pandas 基础，如缺乏基础，可额外学习相关前置课程。 本课程被认为是学习回归和预测的优秀途径。
Welcome to the course Master Regression and Feedforward Networks!This course will teach you to master Regression, Regression analysis, and Prediction with a large number of advanced Regression techniques for purposes of Prediction and Machine Learning Automatic Model Creation, so-called true machine intelligence or AI.You will learn to handle advanced model structures and eXtreme Gradient Boosting Regression for prediction tasks. You will learn modeling theory and several useful ways to prepare a dataset for Data Analysis with Regression Models.You will learn to:Master Regression, Regression analysis, and Prediction both in theory and practiceMaster Regression models from simple linear Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models plus XGBoost RegressionUse Machine Learning Automatic Model Creation and Feature SelectionUse Regularization of Regression models and to regularize regression models with Lasso and Ridge RegressionUse Decision Tree, Random Forest, XGBoost, and Voting Regression modelsUse Feedforward Multilayer Networks and Advanced Regression model StructuresUse effective advanced Residual analysis and tools to judge models' goodness-of-fit plus residual distributions.Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and PythonCloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.Option: To use the Anaconda Distribution (for Windows, Mac, Linux)Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages - golden nuggets to improve your quality of work life.And much more…This course is an excellent way to learn to master Regression and Prediction!Regression and Prediction are the most important and commonly used tools for modeling, prediction, AI, and forecasting.This course is designed for everyone who wants tolearn to master Regression and Predictionlearn about Automatic Model Creationlearn advanced Data Science and Machine Learning plus improve their capabilities and productivityRequirements:Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommendedAccess to a computer with an internet connectionThe course only uses costless softwareWalk-you-through installation and setup videos for Cloud computing and Windows 10/11 is includedSome Python and Pandas skills are necessary. If you lack these, the course "Master Regression and Prediction with Pandas and Python" includes all knowledge you need.This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Regression and Prediction.Enroll now to receive 10+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
