17 short tutorials all data scientists should read
Posted by Armando Brito Mendes | Filed under estatística, materiais para profissionais
Excelentes textos fundamentais para cientistas dos dados
Here’s the list:
- Practical illustration of Map-Reduce (Hadoop-style), on real data
- A synthetic variance designed for Hadoop and big data
- Fast Combinatorial Feature Selection with New Definition of Predict…
- A little known component that should be part of most data science a…
- 11 Features any database, SQL or NoSQL, should have
- Clustering idea for very large datasets
- Hidden decision trees revisited
- Correlation and R-Squared for Big Data
- Marrying computer science, statistics and domain expertize
- New pattern to predict stock prices, multiplies return by factor 5
- What Map Reduce can’t do
- Excel for Big Data
- Fast clustering algorithms for massive datasets
- Source code for our Big Data keyword correlation API
- The curse of big data
- How to detect a pattern? Problem and solution
- Interesting Data Science Application: Steganography
Related link: The Data Science Toolkit
Tags: análise de dados, big data, captura de conhecimento, data mining, Excel, R-software
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