Write Your Own R Packages
This post is to write my own util package to wrap all my udfs with a neat documentation.
Recent posts
Build A Simple Machine Translator encoder-decoder framework with lstm
use encoder decoder arthitecture to translate a foreign language
Implement DeepFM model in Keras
Introduction Wide and deep architect has been proven as one of deep learning applications combining memorization and generatlization in areas such as search and recommendation. Google released its wide&deep learning in 2016. wide part: helps to memorize the past behaviour for specific choice deep part: embed into low dimension, help to discover new user, product combinations Later, on top of wide & deep learning, deepfm was developed combining DNN model and Factorization machi...
Set up Superset on ubuntu 16.04 LTS
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application. Compared with business-focused BI tool like Tableau, superset is more technology-navy. It supports more types of visualization and able to work in distributed manner to boost the query performance. Most importantly, it is free of charge! An example dashboard: Let’s go and set it up. create a virtualenv Assume Anaconda is installed for python management. # create a virtualenv with python ...
Not so basic Keras tutorial for R
The basic tutorial of Keras for R is provided by keras here, which simple and fast to get started. But very soon, I realize this basic tutorial won’t meet my need any more, when I want to train larger dataset. And this is the tutorial I’m going to discuss about keras generators, callbacks and tensorboard. Keras Installation If you haven’t got your keras in R, just follow the steps at below: devtools::install_github("rstudio/keras") library(keras) install_keras() MNIST handwriting recogniti...