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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-with-javascript/
课程评论：没有评论
课程名称：使用JavaScript进行机器学习 课程概述：机器学习是未来的趋势，未来的每一个行业都将受到其影响。本课程将为您提供一个全面的机器学习入门，让您掌握这一颠覆性力量，使您能够理解并应用该领域的各种子学科。与使用Python或R学习机器学习相比，使用JavaScript更为简单。Python虽然流行，但其复杂性可能会妨碍新手的学习。而JavaScript不仅易于理解，还能够让您构建各种应用，如单页应用或浏览器扩展，拓展创新的使用案例。 课程重点： - 理解常见机器学习算法背后的数学和编程技术 - 使用Tensorflow JS库构建强大的应用 - 开发在浏览器或Node.js中的程序 - 编写清晰、易于理解的机器学习代码 - 学习线性代数基础，以加快基于矩阵操作的代码执行 - 灵活应用常见算法以满足独特需求 - 使用自定义绘图库绘制分析结果 - 高效的数据加载技术，适用于浏览器和Node.js环境 无论您是否有数学背景，本课程将确保以易于理解的方式讲解，将深奥的数学概念转化为易于理解的内容。选择本课程，您将为进入机器学习的世界做好准备，掌握生成实际项目和应用所需的工具和知识。
If you're here, you already know the truth: Machine Learning is the future of everything.In the coming years, there won't be a single industry in the world untouched by Machine Learning. A transformative force, you can either choose to understand it now, or lose out on a wave of incredible change. You probably already use apps many times each day that rely upon Machine Learning techniques. So why stay in the dark any longer?There are many courses on Machine Learning already available. I built this course to be the best introduction to the topic. No subject is left untouched, and we never leave any area in the dark. If you take this course, you will be prepared to enter and understand any sub-discipline in the world of Machine Learning.A common question - Why Javascript? I thought ML was all about Python and R?The answer is simple - ML with Javascript is just plain easier to learn than with Python. Although it is immensely popular, Python is an 'expressive' language, which is a code-word that means 'a confusing language'. A single line of Python can contain a tremendous amount of functionality; this is great when you understand the language and the subject matter, but not so much when you're trying to learn a brand new topic.Besides Javascript making ML easier to understand, it also opens new horizons for apps that you can build. Rather than being limited to deploying Python code on the server for running your ML code, you can build single-page apps, or even browser extensions that run interesting algorithms, which can give you the possibility of developing a completely novel use case!Does this course focus on algorithms, or math, or Tensorflow, or what?!?!Let's be honest - the vast majority of ML courses available online dance around the confusing topics. They encourage you to use pre-build algorithms and functions that do all the heavy lifting for you. Although this can lead you to quick successes, in the end it will hamper your ability to understand ML. You can only understand how to apply ML techniques if you understand the underlying algorithms.That's the goal of this course - I want you to understand the exact math and programming techniques that are used in the most common ML algorithms. Once you have this knowledge, you can easily pick up new algorithms on the fly, and build far more interesting projects and applications than other engineers who only understand how to hand data to a magic library.Don't have a background in math? That's OK! I take special care to make sure that no lecture gets too far into 'mathy' topics without giving a proper introduction to what is going on.A short list of what you will learn:Advanced memory profiling to enhance the performance of your algorithmsBuild apps powered by the powerful Tensorflow JS libraryDevelop programs that work either in the browser or with Node JSWrite clean, easy to understand ML code, no one-name variables or confusing functionsPick up the basics of Linear Algebra so you can dramatically speed up your code with matrix-based operations. (Don't worry, I'll make the math easy!)Comprehend how to twist common algorithms to fit your unique use casesPlot the results of your analysis using a custom-build graphing libraryLearn performance-enhancing strategies that can be applied to any type of Javascript codeData loading techniques, both in the browser and Node JS environments
