2018.10.13. 데이터 사이언스 뉴스레터

데이터 사이언스 뉴스레터 (wordcloud)

Our Content Library Growth in the Past 3 Months
Keyword(freq): project(6), effort(2), improvement(2), instructor(2), learner(2), mode(2), skill(2), woman(2), dimension(1), exercise(1)
How is content created at DataCamp?
Keyword(freq): instructor(16), project(5), skill(4), student(4), role(3), background(2), developer(2), perform(2), recruiter(2), specification(2)
Andrew Gelman discusses election forecasting and polling. (Transcript)
Keyword(freq): statistics(29), poll(16), survey(13), pollster(11), number(10), assumption(9), politician(7), state(7), challenge(6), fluctuation(6)

A Step-by-Step Introduction to the Basic Object Detection Algorithms (Part 1)
Keyword(freq): region(21), box(11), object(11), algorithm(8), map(7), step(5), shape(4), image(3), proposal(3), size(3)
An Introduction to Random Forest using the fastai Library (Machine Learning for Programmers <U+2013> Part 1)
Keyword(freq): prediction(13), value(13), column(11), tree(11), point(10), row(9), model(8), sample(7), variable(6), feature(5)
Simplifying Data Preparation and Machine Learning Tasks using RapidMiner
Keyword(freq): column(17), result(7), set(7), baye(5), model(5), change(4), flight(4), prediction(4), step(4), analytics(3)

How to Load, Visualize, and Explore a Complex Multivariate Multistep Time Series Forecasting Dataset
Keyword(freq): variable(95), chunk(50), observation(43), site(30), plot(24), model(17), value(15), column(10), row(10), time(10)
How to Develop LSTM Models for Multi-Step Time Series Forecasting of Household Power Consumption
Keyword(freq): model(28), feature(16), step(15), input(13), unit(11), network(10), result(10), kilowatt(9), observation(9), time(8)
How to Develop Convolutional Neural Networks for Multi-Step Time Series Forecasting
Keyword(freq): model(21), input(14), layer(13), step(12), variable(12), network(11), observation(10), result(10), feature(8), prediction(7)