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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-classification/
课程评论：没有评论
课程名称：Python中的机器学习分类训练营 课程概述：你准备好掌握机器学习技术并开始你的数据科学家职业生涯了吗？这门课程正是为你而设！机器学习是2022年最重要的技能之一，根据PayScale的数据，在美国的平均薪资超过114,000美元。在过去两年中，机器学习职位数量增长了约600%，预计到2025年将继续增长。 本课程将为学员提供最先进的机器学习分类技术的知识和实践经验，包括： - 逻辑回归 - 决策树 - 随机森林 - 朴素贝叶斯 - 支持向量机（SVM） 我们将从零开始建立10个项目，使用真实的世界数据集。项目示例包括： - 构建电子邮件垃圾邮件分类器。 - 进行情感分析并分析亚马逊Alexa产品的客户评价。 - 根据乘客特征预测泰坦尼克号的生存率。 - 预测客户对Facebook上定向营销广告的行为。 - 根据年龄和401K储蓄等特征预测银行客户的退休资格。 - 预测癌症和脊柱后凸疾病。 - 检测信用卡交易中的欺诈。 课程亮点： - 本综合性机器学习课程包含75多个高清录制视频，总时长超过11小时。 - 包含10个实际操作的Python编程项目，学员可以将其添加到个人项目集。 - 没有复杂的数学，我们将以简单清晰的方式讲解理论和直觉。 - 提供所有的Jupyter笔记本（代码）和幻灯片。 - 本课程汇集了超过10年的机器学习和深度学习领域的学术与工业经验。 报名参加本课程后，学员将掌握机器学习分类模型，能够将这些技能直接应用于解决现实世界的挑战。
Are you ready to master Machine Learning techniques and Kick-off your career as a Data Scientist?!You came to the right place!Machine Learning is one of the top skills to acquire in 2022, with an average salary of over $114,000 in the United States, according to PayScale! Over the past two years, the total number of ML jobs has grown around 600 percent and is expected to grow even more by 2025.This course provides students with the knowledge and hands-on experience of state-of-the-art machine learning classification techniques such asLogistic RegressionDecision TreesRandom ForestNaïve BayesSupport Vector Machines (SVM)This course will provide students with knowledge of key aspects of state-of-the-art classification techniques. We are going to build 10 projects from scratch using a real-world dataset. Here's a sample of the projects we will be working on:Build an e-mail spam classifier.Perform sentiment analysis and analyze customer reviews for Amazon Alexa products.Predict the survival rates of the titanic based on the passenger features. Predict customer behavior towards targeted marketing ads on Facebook.Predicting bank clients' eligibility to retire given their features such as age and 401K savings. Predict cancer and Kyphosis diseases.Detect fraud in credit card transactions.Key Course Highlights: This comprehensive machine learning course includes over 75 HD video lectures with over 11 hours of video content.The course contains 10 practical hands-on python coding projects that students can add to their portfolio of projects.No intimidating mathematics, we will cover the theory and intuition in a clear, simple, and easy way.All Jupyter notebooks (codes) and slides are provided. 10+ years of experience in machine learning and deep learning in both academic and industrial settings have been compiled in this course. Students who enroll in this course will master machine learning classification models and can directly apply these skills to solve challenging real-world problems.
