FASHION_MNIST_DAY1_with_Python FASHION MNIST with Python (DAY 1)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST) Datasets¶ Importing numpy, pandas, pyplot¶ In [1]: import numpy as np import pandas as pd import matplotlib.pyplot as plt Loading datasets¶ In [2]: data_train = pd.read_csv("..\\datasets\\fashion-mnist_train.csv") data_test = pd.read_csv("..\..
Building Web App with Shiny in R - Day 2 Building Web App with Shiny in R - Day 2 출처 https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny (Building Web Applications in R with Shiny, DataCamp, Mine Cetinkaya-Rundel) 참고자료 https://www.rstudio.com/resources/cheatsheets/ (Rstudio Cheat Sheets) https://shiny.rstudio.com/ (Shiny homepage) Building Web App with Shiny in R - Day 2. ..
Building Web App with Shiny in R - Day 1 Building Web App with Shiny in R - Day 1 참고자료 https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny (Building Web Applications in R with Shiny, DataCamp, Mine Cetinkaya-Rundel) https://www.rstudio.com/resources/cheatsheets/ (Rstudio Cheat Sheets) https://shiny.rstudio.com/ (Shiny homepage) http://stat.ethz.ch/R-manual/R-devel/library/..
Recurrent Neural Network (ver.Python) 참고자료¶https://www.tensorflow.org (TensorFlow) 출처¶https://medium.com/@erikhallstrm/hello-world-rnn-83cd7105b767 (How to build a Recurrent Neural Network in TensorFlow (1/7), Erik Hall strom) 함께보기¶Recurrent Neural Network (ver.R) Recurrent Neural Network (ver.Python)¶ In [1]: import tensorflow as tf import numpy as np import matplotlib.pyplot as plt num_epochs ..
Autoencoder (ver.Python) DATA SET 출처¶http://archive.ics.uci.edu/ml/datasets/Iris (UCI, Iris Data Set)https://gist.githubusercontent.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv (Github, Iris Data Set) 참고자료¶https://www.tensorflow.org (TensorFlow) 함께보기¶Autoencoder (ver.R) Clustering using Autoencoder (ver.Python)¶ Iris¶ In [1]: import pandas as pd In [2]: iris = pd.read_c..
Manipulating Data in Python3 with the Pandas Manipulating Data in Python3 with the Pandas.¶ https://www.kaggle.com/rtatman/manipulating-data-with-the-tidyverse/notebook (Manipulating Data with the Tidyverse, Rachael Tatman)https://www.kaggle.com/crawford/agricultural-survey-of-african-farm-households (dataset: Agricultural Survey of African Farm Households)https://www.kaggle.com/learn/pandas (Pa..
Manipulating Data in R with the Tidyverse Manipulating Data in R with the Tidyverse.¶ https://www.kaggle.com/rtatman/manipulating-data-with-the-tidyverse/notebook (Manipulating Data with the Tidyverse, Rachael Tatman)https://www.kaggle.com/crawford/agricultural-survey-of-african-farm-households (dataset: Agricultural Survey of African Farm Households)https://www.tidyverse.org/ (Tidyverse)https:/..
Tensorflow for R GPU installation on Ubuntu16.04 Tensorflow for R GPU installation on Ubuntu16.04 https://tensorflow.rstudio.com/installation_gpu.html https://www.tensorflow.org/install/install_linux http://docs.nvidia.com/cuda/cuda-installation-guide-linux/#axzz4VZnqTJ2A https://developer.nvidia.com/cudnnhttps://cloud.r-project.org/ Tensorflow-GPU 설치 on Ubuntu16.04 1 “CUDA® Toolkit 8.0” Install..
Tensorflow-GPU installation on Ubuntu16.04 Tensorflow-GPU installation on Ubuntu16.04 https://www.tensorflow.org/install/install_linuxhttp://docs.nvidia.com/cuda/cuda-installation-guide-linux/#axzz4VZnqTJ2Ahttps://developer.nvidia.com/cudnn Tensorflow for R GPU버전 설치 on Ubuntu16.04 1 “CUDA® Toolkit 8.0” Installation 1.1 Pre-Installation actions. 1.1.1 Verify You Have a CUDA-Capable GPU 1.1.2 Veri..
Logistic Regression in RHadoop Logistic Regression in RHadoop library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(rhdfs) ## Loading required package: rJava ## ## HADOOP_CMD=/home/stat/hadoop/hadoop-2.7.4/bin/hadoop ## #..