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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-statistical-methods-machine-learning-data-science/
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课程名称：Python数据科学与机器学习统计学 课程概述：本课程非常适合希望掌握数据科学和机器学习所需统计方法的学习者。学习统计学是成为专业数据科学家的一个重要环节。然而，许多数据科学学习者专注于Python的学习，而忽略或推迟统计学的学习。缺乏针对数据科学和机器学习的统计学资源和课程是其中一个原因。统计学是一个广泛的领域，但对于数据科学学习者来说，并非所有统计学知识都是必需的。这使得学习者在学习统计学时感到困惑，不知道从何开始，以及哪些统计主题与数据科学最相关。此课程旨在填补这一空白。 本课程适合没有统计学背景的初学者或希望扩展统计学知识的学习者。我将课程组织成一个视频图书馆，供您将来参考。每一讲都覆盖一个具体主题。在这门全面的课程中，我会指导您学习数据分析和数据建模常用的基本统计方法。该课程相当于大学级统计学课程，通常需要花费数千美元，而在这里，您有机会以极低的成本学习所有相关知识！课程包含77个高清讲座，许多习题，以及两个项目和解决方案。所有材料均以详细的可下载笔记本形式提供。 大多数学生关注于学习数据科学的Python代码，但这并不足以成为一名熟练的数据科学家。您还需要理解Python方法的统计基础。虽然可以在Python中轻松创建模型和数据分析，但要能够选择正确的方法或找到最佳模型，您需要理解在这些模型中使用的统计方法。本课程将涵盖以下多个重要主题： - 数据类型与结构 - 探索性数据分析 - 集中趋势度量 - 离散度量 - 数据分布视觉化 - 关联性、散点图和热图 - 数据分布与数据抽样 - 数据缩放与转换 - 置信区间 - 机器学习评估指标 - 机器学习模型验证技术 立即注册课程，掌握数据科学所需的统计学基础知识！
This course is ideal for you if you want to gain knowledge in statistical methods required for Data Science and machine learning!Learning Statistics is an essential part of becoming a professional data scientist. Most data science learners study python for data science and ignore or postpone studying statistics. One reason for that is the lack of resources and courses that teach statistics for data science and machine learning.Statistics is a huge field of science, but the good news for data science learners is that not all statistics are required for data science and machine learning. However, this fact makes it more difficult for learners to study statistics because they are not sure where to start and what are the most relevant topics of statistics for data science.This course comes to close this gap.This course is designed for both beginners with no background in statistics for data science or for those looking to extend their knowledge in the field of statistics for data science.I have organized this course to be used as a video library for you so that you can use it in the future as a reference. Every lecture in this comprehensive course covers a single topic.In this comprehensive course, I will guide you to learn the most common and essential methods of statistics for data analysis and data modeling.My course is equivalent to a college-level course in statistics for data science and machine learning that usually cost thousands of dollars. Here, I give you the opportunity to learn all that information at a fraction of the cost! With 77 HD video lectures, many exercises, and two projects with solutions.All materials presented in this course are provided in detailed downloadable notebooks for every lecture.Most students focus on learning python codes for data science, however, this is not enough to be a proficient data scientist. You also need to understand the statistical foundation of python methods. Models and data analysis can be easily created in python, but to be able to choose the correct method or select the best model you need to understand the statistical methods that are used in these models. Here are a few of the topics that you will be learning in this comprehensive course:· Data Types and Structures· Exploratory Data Analysis· Central Tendency Measures· Dispersion Measures· Visualizing Data Distributions· Correlation, Scatterplots, and Heat Maps· Data Distribution and Data Sampling· Data Scaling and Transformation· Data Scaling and Transformation· Confidence Intervals· Evaluation Metrics for Machine Learning· Model Validation Techniques in Machine LearningEnroll in the course and gain the essential knowledge of statistical methods for data science today!
