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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-complete-linear-and-logistic-regression-course-in-python/
课程评论：没有评论
**课程名称：Python 完整线性与逻辑回归课程** **课程概述：** 本课程专为对机器学习、深度学习和人工智能感兴趣的学习者设计。课程由一位经验丰富的软件工程师教授，旨在帮助您掌握线性回归和逻辑回归这两个机器学习中的核心概念。通过深入浅出的讲解和大量的实践练习，您将学习应用 Scikit-learn、Pandas、TensorFlow、Keras、Matplotlib、Seaborn 等工具和库，理解并实践 Lasso、Ridge、Elastic Net 回归、多元线性回归以及 TensorFlow Keras API。课程还将引导您了解朴素贝叶斯算法，并提供导入UCI数据集的实操。 **核心内容：** * **线性回归：** 包括多元和多变量线性回归，以及 Lasso、Ridge 和 Elastic Net 等正则化技术。 * **逻辑回归：** 详细讲解逻辑回归及其在机器学习中的应用。 * **Python 工具与库：** 深入学习 Google Colab, Scikit-learn, Pandas, TensorFlow, Keras, Matplotlib, Seaborn 等。 * **真实世界项目：** 通过糖尿病、乳腺癌、房价预测和 MNIST 手写数字识别等大型项目，巩固理论知识并提升实践能力。 * **数据导入：** 学习如何从 UCI 存储库导入数据。 **学习目标：** 完成本课程后，您将对线性回归和逻辑回归有深刻的理解，并具备使用 Python 进行模型构建和分析的能力，这将大大提升您在数据科学领域的就业和职业发展机会。
Are you interested in Machine Learning, Deep Learning, and Artificial Intelligence? Then this course is for you!A software engineer has designed this course. With the experience and knowledge I gained throughout the years, I can share my knowledge and help you learn complex theories, algorithms, and coding libraries.I will walk you into the world of the Naive Bayes Algorithm. These are fundamental concepts in machine learning, deep learning, and artificial intelligence. Understanding these basic concepts makes it easier to understand more complex concepts in machine learning, deep learning, and artificial intelligence. There are no courses out there that cover Naive Bayes Algorithm. However, Naive Bayes Algorithm techniques are used in many applications. So it is essential to learn and understand Linear and Logistic Regression. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.This course is fun and exciting, but at the same time, we dive deep into Linear and Logistic Regression. Throughout the brand new version of the course, we cover tons of tools and technologies, including:Google ColabScikit-learnLogistic Regression.Linear Regression.SeabornLasso and Ridge RegressionKeras.Pandas.TensorFlow. TensorBoardMatplotlib.Elastic Net RegressionImport data from the UCI repository.Multiple and multivariate linear regression.TensorFlow Keras APIMoreover, the course is packed with practical exercises based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your models. There are several big projects in this course. These projects are listed below:Diabetes project.Breast Cancer Project.Housing project.MNIST Project.By the end of the course, you will have a deep understanding of Linear and Logistic Regression, and you will get a higher chance of getting promoted or a job by knowing Linear and Logistic Regression.
