Intelligence artificielle et données
488 documents à télécharger gratuitement
Cours, examens, TD, TP et exercices de intelligence artificielle et données. Thèmes couverts : machine learning, apprentissage automatique, big data, data science, fouille de données.
Ce document présente une introduction à l'intelligence artificielle, définissant son but et abordant des concepts fondamentaux comme le test de Turing et l'argument de la chambre chinoise. Il explore deux écoles de pensée sur l'intelligence des machines et fournit des exemples concrets, comme le jeu d'échecs, pour illustrer ces idées. La discussion inclut également un bref historique de l'IA de la période 1945-1955.
This document presents a series of exercises focused on problem representation and resolution techniques in artificial intelligence. It covers state space representation for various problems, including the monkey and bananas problem, robot navigation, and graph representation of the cube universe problem. It requires the application of depth-first, breadth-first, hill climbing, best first, and branch and bound algorithms.
This document discusses the development of classification methods based on formal concept analysis using the WEKA platform. It emphasizes the importance of decision-making in data handling and showcases various data mining techniques. The presentation concludes with perspectives on future applications and methodologies.
This document contains highly fragmented, unintelligible, and malformed content, presenting significant challenges for data extraction and meaningful interpretation. The text includes symbols, disjointed phrases, repetitive patterns, and corrupted segments, reducing clarity. Despite such challenges, the document provides evidence of various attempts to form coherent phrases, although the exact subject and purpose remain ambiguous. The document resembles a corrupted or highly coded dataset meant for testing text parsing capabilities.
This document introduces the field of business intelligence (BI) and data warehousing, addressing the need for extracting actionable insights from large datasets supporting decision-making processes. It outlines the evolution of data-driven decision systems (e.g., OLAP, ERP) and compares operational computing (OLTP) with decision-oriented computing (OLAP). Challenges in data coherency, heterogeneity, and modeling are discussed. Additionally, it highlights methodologies, tools (e.g., ETL, data mining), and platforms (e.g., SAP, Oracle) critical for successful BI projects, focusing on tools t...
This document outlines the design and implementation of a BI solution integrated with Sage ERP. The methodology involves extracting and consolidating enterprise data into dashboards for better decision-making. Data is processed through ETL tools, emphasizing database integrity and visualization via tools like Tableau. The solution aims to enhance organizational performance metrics and support better strategic decisions.
This document details the design of a business intelligence solution for companies using Sage ERP. It involves creating interactive and automatically generated dashboards based on the Sage database. A preliminary analysis of Sage functionalities, manual dashboard practices, and BI principles guided the development. The resulting solution assists companies in making strategic decisions by leveraging generated reports and dashboards.
The document explains the process of classification using decision trees, starting from traversing nodes to reach a decision at leaves. It details the ID3 algorithm, emphasizing entropy and information gain for optimal attribute selection at each node. Practical examples illustrate the construction of decision trees, including scenarios of choosing attributes like age, income, and gender, and summarizing classification pathways. Additionally, the limitations of the greedy nature of ID3 and extensions to regression trees using variance minimization are discussed.