From 225a730e2581a0e0fb98eab75971123bf21051c5 Mon Sep 17 00:00:00 2001 From: GTTeixeira Date: Sun, 3 Dec 2017 18:32:51 -0200 Subject: [PATCH] Criado Readme.md --- README1.md | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 README1.md diff --git a/README1.md b/README1.md new file mode 100644 index 0000000..89b3b48 --- /dev/null +++ b/README1.md @@ -0,0 +1,23 @@ +#Machine Learning com Scikit Learn. + +Tutorial para iniciantes em portugues, usando a biblioteca Scikit Learn. + +O objetivo deste tutorial é introduzir as principais funcionalidades da biblioteca Scikit Learn , em python. + +Este tutorial requer os seguintes pacotes: + +Python versão 3.3+. +numpy versão 1.5+: http://www.numpy.org/ +scipy versão 0.10+: http://www.scipy.org/ +matplotlib versão 1.3+: http://matplotlib.org/ +scikit-learn versão 0.14+: http://scikit-learn.org. + +Dataset utilizado. Fonte: + +https://archive.ics.uci.edu/ml/machine-learning-databases/concrete/compressive/ + +Concrete Compressive Strength Data Type: multivariate + +Abstract: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. These ingredients include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, and fine aggregate. + +Sources: Original Owner and Donor Prof. I-Cheng Yeh Department of Information Management Chung-Hua University, Hsin Chu, Taiwan 30067, R.O.C. e-mail:icyeh@chu.edu.tw