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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-and-machine-learning-course/
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课程名称：人工智能与机器学习课程 课程概述： 本课程强调了人工智能（AI）的重要性，其核心在于通过创建和应用算法，模仿人类智能过程。简单来说，人工智能旨在使计算机像人类一样思考和行动。要实现这一目标，需要三个关键组件：计算系统、数据及其管理、以及先进的人工智能算法（代码）。所需的结果越接近人类行为，所需的数据和处理能力也就越高。 人工智能的重要性： 在当今社会，产生的数据量远远超过人类吸收、解读和基于这些数据进行复杂决策的能力。人工智能是所有计算机学习的基础，也是未来复杂决策的关键。例如，尽管井字棋有255,168种独特的走法，大多数人仍能撑过，但五子棋等更复杂的游戏，会有超过500 quintillion种可能的走法，计算机能够高效计算这些组合，以得出最佳决策。 人工智能的应用： 人工智能在日常生活中有许多实际应用，例如金融服务中的欺诈检测、零售购票预测和在线客户支持等。具体实例包括： - **欺诈检测**：金融服务行业通过人工智能来评分信用申请，理解信用状况，并利用更高级的AI引擎实时监控和检测欺诈性支付卡交易。 - **虚拟客户助手（VCA）**：呼叫中心使用VCA预测和响应客户咨询，从而减少人力干预。语音识别与模拟人类对话的结合成为客户服务的第一接触点。当聊天机器人无法理解客户问题时，人工客服会介入并直接沟通。 机器学习： 机器学习是人工智能的一个子集，提供统计方法和算法，使计算机能够自动从先前的经验和数据中学习，并根据这些学习调整自身行为。 综上所述，本课程将指导学员深入了解人工智能和机器学习的基础知识，并掌握其在现实世界中的应用。
Artificial intelligence (AI) is the basis for mimicking human intelligence processes through the creation and application of algorithms built into a dynamic computing environment. Stated simply, AI is trying to make computers think and act like humans.Achieving this end requires three key components:Computational systemsData and data managementAdvanced AI algorithms (code)The more humanlike the desired outcome, the more data and processing power required.Why is artificial intelligence important?Today, the amount of data that is generated, by both humans and machines, far outpaces humans' ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making. As an example, most humans can figure out how to not lose at tic-tac-toe (noughts and crosses), even though there are 255,168 unique moves, of which 46,080 end in a draw. Far fewer folks would be considered grand champions of checkers, with more than 500 x 1018, or 500 quintillion, different potential moves. Computers are extremely efficient at calculating these combinations and permutations to arrive at the best decision. AI (and its logical evolution of machine learning) and deep learning are the foundational future of business decision making.Requirement of Artificial intelligence Applications of AI can be seen in everyday scenarios such as financial services fraud detection, retail purchase predictions, and online customer support interactions. Here are just a few examples:Fraud detection. The financial services industry uses artificial intelligence in two ways. Initial scoring of applications for credit uses AI to understand creditworthiness. More advanced AI engines are employed to monitor and detect fraudulent payment card transactions in real time.Virtual customer assistance (VCA). Call centers use VCA to predict and respond to customer inquiries outside of human interaction. Voice recognition, coupled with simulated human dialog, is the first point of interaction in a customer service inquiry. Higher-level inquiries are redirected to a human.When a person initiates dialog on a webpage via chat (chatbot), the person is often interacting with a computer running specialized AI. If the chatbot can't interpret or address the question, a human intervenes to communicate directly with the person. These noninterpretive instances are fed into a machine-learning computation system to improve the AI application for future interactions.Machine LearningMachine Learning is naturally a subset of AI. It provides the statistical methods and algorithms and enables the machines/computers to learn automatically from their previous experiences and data and allows the program to change its behavior accordingly.
