Introduction to machine learning in 15 hours

Post by: Flavio Source: R-bloggers “In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook,

Statistics for Biologists (Nature.com)

Post by Flavio Lichtenstein. Image Credit: Erin DeWalt. Check out this very nice Web Collection! “There is no disputing the importance of statistical analysis in biological research, but too often it is considered only

Epidemiologia digital (in Portuguese)

Post by Helder. Com as nossas vidas totalmente conectadas pelas redes sociais, surge agora uma nova maneira de monitorar doenças, hábitos e até epidemias na população. E tudo em tempo real. Essa é a

100+ Free Data Science Books

Post by Pedro. Check the LearnDataSci website. “Pulled from the web, here is a our collection of free books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more.

Deep Dream Generator

Post by Pedro. Generate your own deep dream photos and images for free. ABOUT DEEP DREAM Google has spent the last few years teaching computers how to see, understand, and appreciate our world. It’s

Share Your Data Science Narratives In R

Post by Leonardo. Share Your Data Science Narratives In R with the New R Essentials Package Today, we’re excited to announce that the new R Essentials bundle has been created for Anaconda. R Essentials bundles IRKernel, and over 80

Bioinformatics Autodiscovery of Training Materials

Post by Matheus.   BATMat (Bioinformatics Autodiscovery of Training Materials) is a Google-based, open source, automatic search tool for training materials. BATMat helps gain access with one click to filtered and portable information containing

How the hell PCA works?

Post by Pedro and Leonardo.   For those who never understood how Principal Component Analysis works… Start here. Other useful links: here here here and here.     Image credit.      

Command line for dummies

Suggested by Pedro and Helder.   The codeacademy course for starters in command line. Check here.   Also check here (nice cheat sheet): Become a Command Line Ninja With These Time-Saving Shortcuts Image credit

Mathematics for Computer Science

Suggested by Pedro.   “Course Description This course is offered to undergraduates and is an elementary discrete mathematics course oriented towards applications in computer science and engineering. Topics covered include: formal logic notation, induction,

Beyond Bar and Line Graphs

Suggested by Thiago M. Venancio. Very nice read. PLoS Biology paper: Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm Tracey L. Weissgerber , Natasa M. Milic, Stacey J. Winham, Vesna

Useful cheat sheets (#1)

Suggested by Matheus, Pedro and Leonardo. Here are some important cheat sheets.   For statistical tests: click here. For R-based Software: click here. For Big-O complexities of common algorithms used in Computer Science: click

statisticsfun (YouTube channel)

Suggested by Pedro Russo. “Visual learning to help student pass statistics class. Channel includes video lessons on regression, z scores, t statistics, Analysis of Variance (ANOVA), Chi Square, SPSS, Excel and most topics taught

R versus Python (in portuguese)

Post by: Leonardo Gama Navegando a altas horas da madrugada (talvez não devesse estar fazendo isso, mas tudo bem), fui parar em um artigo de um pesquisador que vêm substituindo a maioria das ferramentas que ele usa,