Tabla de Contenidos: “…. -- Chapter 8: Searching, Mining and Visualizing Data -- Introduction -- Geocoding an IP address -- Getting ready -- How to do it -- How to collect IP addresses of Wikipedia edits -- Getting ready -- How to do it -- How it works -- There's more... -- Visualizing contributor location frequency on Wikipedia -- How to do it -- Creating a word cloud from a StackOverflow job listing -- Getting ready -- How to do it -- Crawling links on Wikipedia -- Getting ready -- How to do it -- How it works -- Theres more... -- Visualizing page relationships on Wikipedia -- Getting ready -- How to do it -- How it works -- There's more... -- Calculating degrees of separation -- How to do it -- How it works -- There's more... -- Chapter 9: Creating a Simple Data API -- Introduction -- Creating a REST API with Flask-RESTful -- Getting ready -- How to do it -- How it works -- There's more... -- Integrating the REST API with scraping code -- Getting ready -- How to do it -- Adding an API to find the skills for a job listing -- Getting ready -- How to do it -- Storing data in Elasticsearch as the result of a scraping request -- Getting ready -- How to do it -- How it works -- There's more... -- Checking Elasticsearch for a listing before scraping -- How to do it -- There's more…”

Materias: “…Data mining…”

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Tabla de Contenidos: “…Consumable Massive Facts Analytics -- 2.1.2. Allotted Records Mining Algorithms -- 2.1.3. Gadget Failure -- 2.1.4. …”

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Tabla de Contenidos: “…Web 2.0 and the Arrival of Big Data -- Unstructured Data -- Semi-Structured Data -- Metadata -- The Composition of Data: Then and Now -- The Current State of the Data Union -- The Enterprise and the Brave New Big Data World -- The Data Disconnect -- Big Tools and Big Opportunities -- Summary -- Notes -- Chapter 2 Demystifying Big Data -- Characteristics of Big Data -- Big Data Is Already Here -- Big Data Is Extremely Fragmented -- Big Data Is Not an Elixir -- Small Data Extends Big Data -- Big Data Is a Complement, Not a Substitute -- Big Data Can Yield Better Predictions -- Big Data Giveth-and Big Data Taketh Away -- Big Data Is Neither Omniscient Nor Precise -- Big Data Is Generally Wide, Not Long -- Big Data Is Dynamic and Largely Unpredictable -- Big Data Is Largely Consumer Driven -- Big Data Is External and "Unmanageable" in the Traditional Sense -- Big Data Is Inherently Incomplete -- Big Overlap: Big Data, Business Intelligence, and Data Mining -- Big Data Is Democratic -- The Anti-Definition: What Big Data Is Not -- Summary -- Notes -- Chapter 3 The Elements of Persuasion: Big Data Techniques…”

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