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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-with-python-data-science-for-beginners/
课程评论：没有评论
课程名称：使用Python进行机器学习：初学者的数据科学 概述：机器学习是计算机科学的一个领域，使计算机能够在没有明确编程的情况下进行学习。机器学习在2017年是需求量最大、薪资最高的职业，预计这一趋势将在未来几年持续。根据Glassdoor和Indeed的数据，机器学习的平均工资为120,000美元，这使其成为获取高薪工作的绝佳选择。本课程旨在面向零编程经验的初学者和希望转向数据科学的经验丰富的开发人员！课程结束时，您将能够掌握使用Python进行机器学习，解密人工智能、机器学习和数据科学，探索并定义机器学习用例，制定ML商业解决方案蓝图，了解Spyder、Pandas和NumPy的使用，实施数据工程，进行探索性数据分析，了解统计学和概率分布，掌握机器学习方法论，理解监督学习，实施简单和多元线性回归、决策树、回归与分类模型评估、交叉验证、超参数和集成建模，随机森林和XGBoost等内容。 学习机器学习将是推动您职业发展的重要途径，并将为您打开新的工作机会的大门。课程提供100%退款保证。如果您不满意，可以在30天内申请退款，保证全额退还，无条件。 欢迎查看课程描述和演示视频，我们期待在课程中见到您！
Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine Learning is the most in-demand and Highest Paying job of 2017 and the same trend will follow for the coming years. With an average salary of $120,000 (Glassdoor and Indeed), Machine Learning will help you to get one of the top-paying jobs. This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science! At the end of the course you will be able to Master Machine Learning using PythonDemystifying Artificial Intelligence, Machine Learning, Data ScienceExplore & Define a ML use caseML Business Solution BlueprintExplore Spyder, Pandas and NumPyImplement Data EngineeringExploratory Data Analysis Introduction to Statistics and Probability DistributionsLearn Machine Learning MethodologyUnderstand Supervised Learning Supervised LearningImplement Simple & Multiple Linear RegressionDecision TreesRegression & Classification Model EvaluationCross Validation, Hyperparameter Ensemble ModelingRandom Forest & XGBoost Learning Machine Learning is a definite way to advance your career and will open doors to new Job opportunities. 100% MONEY-BACK GUARANTEE This course comes with a 30-day money back guarantee. If you're not happy, ask for a refund, all your money back, no questions asked. Feel forward to have a look at course description and demo videos and we look forward to see you inside.
