2018.07.21. 데이터 사이언스 뉴스레터

데이터 사이언스 뉴스레터 (wordcloud)

New Project: Naive Bees: Image Loading and Processing
Keyword(freq): data(5), image(2), classifier(1), prerequisite(1), project(1), researcher(1), species(1), technique(1), transformation(1), NA(NA)
Data Science at McKinsey (Transcript)
Keyword(freq): data(96), analytics(45), tara(33), model(29), decision(16), organization(16), scientist(13), client(10), industry(9), algorithm(8)

FLASH SALE! Get Flat 55% off on our Popular ‘Introduction to Data Science’ Course!
Keyword(freq): data(6), project(3), agent(2), product(2), sale(2), scientist(2), analytics(1), aspect(1), attribute(1), basic(1)
Ultimate Guide: Building a Mask R-CNN Model for Detecting Car Damage (with Python codes)
Keyword(freq): image(7), annotation(4), application(3), car(3), model(3), pixel(3), weight(3), error(2), example(2), layer(2)
MyStory: Step by Step process of How I Became a Machine Learning Expert in 10 Months
Keyword(freq): data(17), topic(11), algorithm(5), skill(5), concept(4), model(4), step(4), detail(3), parameter(3), run(3)
An Introductory Guide to Maximum Likelihood Estimation (with a case study in R)
Keyword(freq): data(21), parameter(14), coefficient(9), ticket(8), distribution(6), observation(4), bfg(3), problem(3), result(3), technique(3)

What is the Difference Between a Batch and an Epoch in a Neural Network?
Keyword(freq): sample(18), epoch(17), parameter(12), batch(10), thank(8), algorithm(6), prediction(6), value(5), network(4), data(3)
The Role of Randomization to Address Confounding Variables in Machine Learning
Keyword(freq): variable(34), experiment(8), data(6), effect(5), method(5), model(5), result(5), experimenter(4), confounder(3), example(3)
All of Statistics for Machine Learning
Keyword(freq): statistics(27), topic(10), data(5), example(4), method(4), comment(3), practitioner(3), student(3), algorithm(2), developer(2)