I think programming languages are called languages for a reason - and I think we all have a native and secondary language
Here's a handy lexicon between R and Python of sorts for your reference. It's sure to be handy, no matter which one is your native language!
π https://lnkd.in/eG-Grrr
#datascience #dataanalysis #python #r
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π£ @Data_Experts
β΄οΈ @AI_Python_EN
Here's a handy lexicon between R and Python of sorts for your reference. It's sure to be handy, no matter which one is your native language!
π https://lnkd.in/eG-Grrr
#datascience #dataanalysis #python #r
βοΈ @AI_Python
π£ @Data_Experts
β΄οΈ @AI_Python_EN
R in Pharmacy? Honestly, I started losing any hope to see the pharmacy turning (even slowly!) towards R. A little has been happening since 1976, when the S (father of R), was born. And even when S, then R, gained the status of an industry standard in widely understood bio-sciences, it has never happened in pharmacy, namely in clinical research. This was -and still is- the kingdom exclusively reigned by SAS The King (with a low % of "supporters", including R).
It was a big shame, but, what could have been done against long years of spread myths, doubt, uncertainty and negative attitude?
Well, this is not that everything was right about R! Serious topics still have to be addressed, including:
1) numerical validation (ideally free, coordinated by, say, R Consortium),
2) support for CDISC-related processes,
3) metadata layer (SAS format/informat),
There are more topics, yet there's no place for details.
And then, about 5 years ago, something started changing. Slowly. More and more top-pharma companies (even FDA!) started talking about their use of R publicly, some even contributed (e.g. Merck's gsDesign tool).
Today I'd like to share with you the news: a new initiative by R Consortium - the "R in Pharma" project. http://rinpharma.com/
#R #statistics
β΄οΈ @AI_Python_EN
π£ @AI_Python_Arxiv
βοΈ @AI_Python
It was a big shame, but, what could have been done against long years of spread myths, doubt, uncertainty and negative attitude?
Well, this is not that everything was right about R! Serious topics still have to be addressed, including:
1) numerical validation (ideally free, coordinated by, say, R Consortium),
2) support for CDISC-related processes,
3) metadata layer (SAS format/informat),
There are more topics, yet there's no place for details.
And then, about 5 years ago, something started changing. Slowly. More and more top-pharma companies (even FDA!) started talking about their use of R publicly, some even contributed (e.g. Merck's gsDesign tool).
Today I'd like to share with you the news: a new initiative by R Consortium - the "R in Pharma" project. http://rinpharma.com/
#R #statistics
β΄οΈ @AI_Python_EN
π£ @AI_Python_Arxiv
βοΈ @AI_Python
The ability to pull/extract data from a website is invaluable in #DataScience. Learn how to collect your own data using #WebScraping in both #Python and #R:
Beginnerβs Guide on Web Scraping in R (using rvest) - https://lnkd.in/fFzU2kw
Beginnerβs guide to Web Scraping in Python (using BeautifulSoup) - https://lnkd.in/fxTKYdA
Web Scraping in Python using Scrapy - https://lnkd.in/fUD_aCi
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv
Beginnerβs Guide on Web Scraping in R (using rvest) - https://lnkd.in/fFzU2kw
Beginnerβs guide to Web Scraping in Python (using BeautifulSoup) - https://lnkd.in/fxTKYdA
Web Scraping in Python using Scrapy - https://lnkd.in/fUD_aCi
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv
#LogisticRegression is the most commonly used classification #algorithm in the industry. Here are 3 articles to understand the nitty-gritty of this technique:
Simple Guide to Logistic Regression in #R - https://lnkd.in/fQHsskA
Building a Logistic Regression model from scratch - https://lnkd.in/fK79Nf5
How to use Multinomial and Ordinal Logistic Regression in R? - https://lnkd.in/fHFHnDq
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv
Simple Guide to Logistic Regression in #R - https://lnkd.in/fQHsskA
Building a Logistic Regression model from scratch - https://lnkd.in/fK79Nf5
How to use Multinomial and Ordinal Logistic Regression in R? - https://lnkd.in/fHFHnDq
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv
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Here's a cheatsheet on Scikit-Learn (machine learning library that provides a range of supervised & unsupervised algorithms in #Python) and Caret package (used for solving any supervised machine learning problem in #R) we would like to share with you. #ScikitLearn #Caret https://lnkd.in/fgfR3FU
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_arXiv