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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-to-machine-learning-for-begineer/
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Coursera 课程：机器学习入门（面向初学者，数据科学方向） 本课程将全面指导您学习 Python 中的监督学习和无监督学习。它涵盖了实际数据科学的所有主要方面，完成本课程后，您将无需再学习其他 Python 数据科学课程或购买相关书籍。 在当今大数据时代，全球公司都利用 Python 来处理海量信息。掌握 Python 中的监督学习和无监督学习，能为您的公司带来竞争优势，并助您职业生涯更上一层楼。 由拥有 3 年以上经验的资深数据科学家 Aakash Singh 授课，他最近还在国际期刊 IJSR 上发表了关于机器学习数据集的研究论文。本课程将帮助您扎实掌握主要的机器学习聚类和分类技术。 无需任何 Python、统计学或机器学习知识。课程将从最实用的 Python 数据科学基础和技术讲起，通过易于理解的动手实践方法，简化并讲解复杂的概念。您将学会使用 NumPy、Pandas 和 Matplotlib 等 Python 包来处理实际数据。 课程包含 Jupyter Notebook 终端的实验环节，通过大量真实案例来增强您的编程实践知识，同时也会讲解必要的理论知识。学完本课程后，您将能够熟练运用 Python 编程，自信地进行机器学习，并能独立开发和实现自己的程序。最重要的是，您将学会如何使用 Python 实践这些技术。课程提供所有使用的数据和脚本，并且讲师会提供全程支持。 立即报名！
HERE IS WHY YOU SHOULD TAKE THIS COURSEThis course completely guides you through both supervised and unsupervised learning using Python. This means this course covers all the main aspects of practical data science, and if you take this course, you can be done with taking other courses or buying books on Python-based data science.In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal.By becoming proficient in supervised and unsupervised learning in Python, you can give your company a competitive edge and boost your career to the next level.LEARN FROM AN EXPERT DATA SCIENTIST WITH 3+ YEARS OF EXPERIENCEMy name is Aakash Singh and I have also recently published my research paper in the International Journal IJSR on Machine Learning Datasets.This course will help you gain a robust grounding in the main machine learning clustering and classification techniques.NO PRIOR PYTHON OR STATISTICS OR MACHINE LEARNING KNOWLEDGE IS REQUIREDYou will start by absorbing the most valuable Python data science basics and techniques.I use easy-to-understand hands-on methods to simplify and address even the most difficult concepts in Python.My course will help you implement the methods using real data obtained from different sources. After taking this course, you will easily use packages like NumPy, Pandas, and Matplotlib to work with real data in Python.We will go through lab sessions on Jupyter Notebook terminal. We will explore lots of real-life examples to increase practical knowledge of programming. We will also cover theoretical sections, which are essential for this course. By the end of this course, you will be able to code in Python and feel confident with machine learning, enabling you to create your own programs and implement them where needed.Most importantly, you will learn to implement these techniques practically using Python. You will have access to all the data and scripts used in this course. Remember, I am always here to support my students.SIGN UP NOW
