课程描述
Machine Learning and AI: Support Vector Machines in Python is a course in which you learn about artificial intelligence, support vector machines, and data science algorithms in the Python language and learn how to classify and regress. The support vector machine is one of the most powerful machine learning models used for classification. Today, there is talk of deep learning everywhere, and this course tries to teach you valuable material in this area.
机器学习和 AI：Python 中的支持向量机是一门课程，您可以在其中学习 Python 语言中的人工智能、支持向量机和数据科学算法，并学习如何进行分类和回归。支持向量机是用于分类的最强大的机器学习模型之一。今天，到处都在谈论深度学习，本课程试图向您传授该领域的宝贵资料。
One of the problems with the support vector machine is that it is theoretically learning, and many students simply skip it. In this training course, we try to show you all the theoretical topics about the support vector machine and how it works in a step-by-step and practical way. We use logistic regression as a starting point and then teach you other SVM topics.
支持向量机的一个问题是它是理论学习，很多同学干脆跳过。在本培训课程中，我们尝试向您展示有关支持向量机的所有理论主题及其如何以循序渐进和实用的方式工作。我们使用逻辑回归作为起点，然后教您其他 SVM 主题。
Courses taught in this course:; 本课程讲授的课程：
- Apply SVM to application software
- 将SVM应用于应用软件
- Understand the theory of machine vector support
- 理解机器向量支持理论
- Work with image recognition software, spam detection, and regression analysis
- 使用图像识别软件、垃圾邮件检测和回归分析
- Build RBF and other neural networks
- 构建 RBF 和其他神经网络
Machine Learning and AI course specifications: Support Vector Machines in Python:; 机器学习和 AI 课程规范：Support Vector Machines in Python：
- English language
- 英语
- Duration: 8 hours and 50 minutes
- 持续时间：8 小时 50 分钟
- Number of lessons: 72
- 课时数：72
- Level of education: Medium
- 教育程度：中等
- Instructor: Lazy Programmer Inc.
- 讲师：Lazy Programmer Inc.
- File format: mp4
- 文件格式：mp4
Machine Learning and AI Course Titles: Support Vector Machines; 机器学习和人工智能课程名称：支持向量机
72 lectures 08:50:20
72 讲 08:50:20
Welcome
4 lectures 18:51
欢迎 4 讲座 18:51
Beginner\’s Corner
7 lectures 46:36
新手园地 7 讲 46:36
Review of Linear Classifiers
7 lectures 50:14
线性分类器回顾 7 个讲座 50:14
Linear SVM
10 lectures 01:06:27
线性 SVM 10 个讲座 01:06:27
Duality
7 lectures 43:47
二元性 7 讲座 43:47
Kernel Methods
9 lectures 51:14
内核方法 9 个讲座 51:14
Implementations and Extensions
8 lectures 54:21
实现和扩展 8 个讲座 54:21
Neural Networks (Beginner\’s Corner 2)
8 lectures 50:24
神经网络（初学者园地 2）8 个讲座 50:24
Appendix / FAQ
12 lectures 02:28:26
附录/常见问题解答 12 讲 02:28:26
Course prerequisites; 课程先决条件
- Calculus, Arithmetic / Geometry Matrix, Basic Probability
- 微积分、算术/几何矩阵、基本概率
- Python and Numpy coding
- Python 和 Numpy 编码
- Logistic Regression
- 逻辑回归
Pictures; 图片
Sample movie; 样片
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Installation guide; 安装指南
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English subtitle
英文字幕
Quality: 720p
画质：720p
