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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-ultimate-beginners-guide-to-ai-and-machine-learning/
课程评论：没有评论
课程名称：《初学者的终极AI与机器学习指南》 课程概述：本课程为任何想要掌握人工智能和机器学习的初学者提供了基本的基础知识。课程将重要的AI概念整合在一起，这些概念在未来很长一段时间内都将具有相关性。掌握任何技能都需要坚实的基础。对于希望在AI和机器学习领域发展职业的人士来说，将从中受益匪浅。此外，非技术专业人士，如市场营销人员和商业分析师等，通过掌握本课程的概念，也能够有效地与数据科学家、机器学习工程师或者数据科学家进行交流与协作。 在本课程中，许多关于人工智能和机器学习的误解得到了澄清。完成课程后，您将清楚地理解AI、机器学习、深度学习、强化学习和深度强化学习之间的区别。课程清晰地解释了机器学习的基本概念，以及机器学习如何在背后运用数学。课程仅涉及到高中数学概念，因为神经网络在机器学习的各个领域广泛使用，且是一种数学函数近似器。因此，课程将涵盖函数的基本知识及其近似的方式，以便解释神经网络。 需要注意的是，本课程不涉及任何编码或复杂数学，总体上旨在为更高级的AI和机器学习课程提供一个基础性铺垫。
This course provides the essential foundations for any beginner who truly wants to master AI and machine learning. Crucial, foundational AI concepts, all bundled into one course. These concepts will be relevant for years to come. Mastering any craft, requires that you have solid foundations. Anyone who is thinking about starting a career in AI and machine learning will benefit from this. Non-technical professionals such as marketers, business analysts, etc. will be able to effectively converse and work with data scientists, machine learning engineers, or even data scientists if they apply themselves to understanding the concepts in this course.Many misconceptions about artificial intelligence and machine learning are clarified in this course. After completing this course, you will understand the difference between AI, machine learning, deep learning, reinforcement learning, deep reinforcement learning, etc.The fundamental concepts that govern how machines learn, and how machine learning uses mathematics in the background, are clearly explained. I only reference high school math concepts in this course. This is because neural networks, which are used extensively in all spheres of machine learning, are mathematical function approximators. I therefore cover the basics of functions, and how functions can be approximated, as part of the explanation of neural networks.This course does not get into any coding, or complex mathematics. This course is intended to be a baseline stepping stone for more advanced courses in AI and machine learning.
