Course Introduction Module 1 This course will give you an introduction to machine learning with the Python programming language. You will learn about supervised learning, unsupervised learning, deep learning, image processing, and generative adversarial networks. You will implement machine learning models ...
IBM Introduction to Machine Learning Specialization [4 courses] (IBM) ['IBM'] https://www.coursera.org/specializations/ibm-intro-machine-learning IBM机器学习入门专业化[4门课程] (IBM) 80 JavaScript Programming with React, Node & MongoDB ['IBM'] https://www.coursera.org/specializations/javascript...
Machine Learning Specialization (DeepLearning.AI) ['DeepLearning.AI', 'Stanford University'] https://www.coursera.org/specializations/machine-learning-introduction 机器学习专业化(DeepLearning.AI) Introduction to Data Science ['IBM'] https://www.coursera.org/specializations/introduction-data-science 数据...
Arthur Samuel (1959). Machine Learning: Field of study that gives computers the ability to learn without being explicitly programmed. 这个定义有点不正式但提出的时间最早,来自于一个懂得计算机编程的下棋菜鸟,编程使得计算机通过不断的对弈,不断地计算布局的好坏来“学习”,从而积累经验,这样,这个计算机程序成...
Introduction: 1、What is Machine Learning? 什么是机器学习? Two definitions of Machine Learning are offered. Arthur Samuel described it as: "the field of study that gives computers the ability to learn without being explicitly programmed." This is an older, informal definition. 这里有两个关于机器...
🟧Introduction to Statistics(斯坦福大学)🟧评分4.5 ➡️ 这门课程由斯坦福大学提供,重点探索性数据分析,了解采样的关键原理,并为多种情况选择合适的显着性检验。 ⏰ 约11小时的在线课程 ➡️ 通过这门课程,你可以学到: 如何收集数据和描述统计 生产数据和抽样 正态近似和二项分布 🟧Machine Learning...
The course starts with an introduction to machine learning, explaining its applications and the different types of machine learning algorithms. Prof. Ng then dives into the mathematical foundations of machine learning, including linear algebra and calculus, which are essential for understanding the ...
深度学习导论(Introduction to Deep Learning)是专项课程系列中的第一部分,这部分包括: 第1周- 最优化理论 第2周- 神经网络导论 第3周- 深度学习图像处理 第4周- 无监督表征学习 第5周- 深度学习文本处理 第6周- 结课项目 本文是第1周的第2份课程笔记:线性模型(上) ...
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction,...
博客园 - 链接:Coursera 学习笔记|Machine Learning by Standford University - 吴恩达 Chapter 1 - Introduction 1.1 Definition Arthur Samuel The field of study that gives computers the ability to learn without being explicitly programmed. Tom Mitchell ...