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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-regression-masterclass-in-python/
课程评论：没有评论
课程名称：Python中的机器学习回归大师班 课程概述：人工智能（AI）革命已经来临！这一技术正以巨大的规模发展，并在医疗、国防、银行、游戏、交通和机器人等行业被广泛应用。机器学习是人工智能的一个子领域，它使得机器能够通过经验改进特定任务的能力。在过去五年中，机器学习已经成为一个极热门的话题，对经验丰富的机器学习工程师和数据科学家的需求不断增长。根据Research and Markets发布的报告，全球人工智能和机器学习技术行业预计从14亿美元增长到88亿美元，并且预测到2020年，人工智能技术领域将创造约230万个就业机会。 本课程的目的是以实用、有趣和简单的方式向学生传授机器学习回归技术的关键方面。回归分析是一种重要的机器学习技术，通过多个独立变量预测连续的（依赖的）变量。回归策略广泛应用于股票市场预测、房地产趋势分析和目标营销活动。 本课程为学生提供了在真实世界数据集上训练机器学习回归模型的实践经验，涵盖了多种技术，包括： - 简单线性回归 - 多元线性回归 - 多项式回归 - 逻辑回归 - 决策树回归 - 岭回归 - 套索回归 - 用于回归分析的人工神经网络 - 回归的关键绩效指标 该课程面向希望掌握机器学习回归模型的学生。推荐具备基础编程知识，但课程早期讲座将广泛覆盖这些主题，因此课程没有先决条件，任何具有基本编程基础的学生均可参加。注册本课程的学生将掌握机器学习回归模型的技能，并能够直接运用这些技能解决现实世界中的挑战性问题。
Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries.Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience. Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years. According to a report released by Research and Markets, the global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020.The purpose of this course is to provide students with knowledge of key aspects of machine learning regression techniques in a practical, easy and fun way. Regression is an important machine learning technique that works by predicting a continuous (dependant) variable based on multiple other independent variables. Regression strategies are widely used for stock market predictions, real estate trend analysis, and targeted marketing campaigns.The course provides students with practical hands-on experience in training machine learning regression models using real-world dataset. This course covers several technique in a practical manner, including:· Simple Linear Regression· Multiple Linear Regression· Polynomial Regression· Logistic Regression· Decision trees regression· Ridge Regression· Lasso Regression· Artificial Neural Networks for Regression analysis· Regression Key performance indicatorsThe course is targeted towards students wanting to gain a fundamental understanding of machine learning regression models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master machine learning regression models and can directly apply these skills to solve real world challenging problems.
