Deeplearning4j Documentation
Posted by Armando Brito Mendes | Filed under materiais para profissionais, software
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O site de um pacote java para deeplearing com montes de info. sobre redes neuronais e afins.
- How To
- Quickstart: Running Examples and DL4J in Your Projects
- Comprehensive Setup Guide
- Build Locally From Master
- Contribute to DL4J (Developer Guide)
- Choose a Neural Net
- Use the Maven Build Tool
- Vectorize Data With Canova
- Build a Data Pipeline
- Run Benchmarks
- Configure DL4J in Ivy, Gradle, SBT etc
- Find a DL4J Class or Method
- Save and Load Models
- Interpret Neural Net Output
- Visualize Data with t-SNE
- Swap CPUs for GPUs
- Customize an Image Pipeline
- Perform Regression With Neural Nets
- Troubleshoot Training & Select Network Hyperparameters
- Visualize, Monitor and Debug Network Learning
- Speed Up Spark With Native Binaries
- Build a Recommendation Engine With DL4J
- Use Recurrent Networks in DL4J
- Build Complex Network Architectures with Computation Graph
- Train Networks using Early Stopping
- Download Snapshots With Maven
- Customize a Loss Function
- Introduction to Neural Networks
- Multilayer Neural Nets
- Tutorials
- Datasets
- Scaleout
- Text
- Resources
- DL4J, Torch7, Theano and Caffe
- Glossary of Terms for Deep Learning and Neural Nets
- Deep Learning’s Accuracy
- DataVec: ETL for ML
- ND4J Backends: How They Work
- Model Zoo
- Unsupervised Learning: Use Cases
- Eigenvectors, PCA, Covariance and Entropy
- Thought Vectors, AI and NLP
- Questions to Ask When Applying DL
- AI, Machine Learning and Deep Learning
- DL and Reinforcement Learning
- Javadoc: DL4J Methods and Classes
- Canova Javadoc: Canova Methods and Classes
- ND4J User Guide
- ND4J Javadoc
- Scala, Spark and Deep Learning
- Further Reading on Deep Learning
- Deep Learning in Other Languages
- Use Cases
- Architecture
- Features
- Roadmap
- About
- Open Data
- Latest Release Notes
Guardar
Tags: análise de dados, big data, data mining, desnvolvimento de software, machine learning
A Growth Hacker’s Journey
Posted by Armando Brito Mendes | Filed under linguagens de programação, software
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Dr. Kirk Borne is a Principal Data Scientist at Booz Allen Hamilton. Previously he was a Professor of Astrophysics and Computational Science in the George Mason University School of Physics, Astronomy, and Computational Sciences. He was at Mason from 2003 to 2015, where he taught and advised students in the graduate and undergraduate Computational Science, Informatics, and Data Science programs. Before Mason, he spent nearly 20 years in positions supporting NASA projects, including an assignment as NASA’s Data Archive Project Scientist for the Hubble Space Telescope, and as Project Manager in NASA’s Space Science Data Operations Office. He has extensive experience in big data and data science, including expertise in scientific data mining and data systems. He has published over 200 articles (research papers, conference papers, and book chapters), and given over 200 invited talks at conferences and universities worldwide. In these roles, he focuses on achieving big discoveries from big data through data science, and he promotes the use of information and data-centric experiences with big data in the STEM education pipeline at all levels. He believes in data literacy for all! Learn more about him at http://kirkborne.net/. You can follow him on Google+ here and on Twitter at @KirkDBorne, where he has been identified as one of the social network’s top big data influencers.
Tags: C \ fortran, SQL
Raynald’s SPSS Tools
Posted by Armando Brito Mendes | Filed under estatística, materiais para profissionais, software
Bons recursos sobre SPSS e ligação com R e Pyton
Raynald’s SPSS Tools
The collection of syntaxes, macros, scripts and hints for better solutions of data management and data analysis problems in IBM SPSS Statistics
Tags: análise de dados, decisão médica, Estat Descritiva, IBM SPSS Statistics, R-software, software estatístico
Random Probability, Mathematical Statistics, Stochastic Processes
Posted by Armando Brito Mendes | Filed under estatística, lições, software
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Um site organizado por temas como um livro com apps interessantes
Welcome!
Random (formerly Virtual Laboratories in Probability and Statistics) is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library. Please read the Introduction for more information about the content, structure, mathematical prerequisites, technologies, and organization of the project. Random is hosted at two sites: www.math.uah.edu/stat/ and www.randomservices.org/stat/. For updates, please follow @randomservices on Twitter.
Basic Information
Expository Chapters
- Foundations
- Probability Spaces
- Distributions
- Expected Value
- Special Distributions
- Random Samples
- Point Estimation
- Set Estimation
- Hypothesis Testing
- Geometric Models
- Bernoulli Trials
- Finite Sampling Models
- Games of Chance
- The Poisson Process
- Renewal Processes
- Stochastic Processes
- Markov Chains
- Brownian Motion
Ancillary Materials
Support and Navigation
Tags: software estatístico
Rice Virtual Lab in Statistics Demos
Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, software
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Pequenas apps em java para demonstrar diferentes temas em estatística
Sampling Distribution Simulation
Normal Approximation to the Binomial Distribution
Confidence Interval on a Proportion
A “Small” Effect Size Can Make a Large Difference
Chi Square Test of Deviations from Expected Frequencies
Reliability and Regression Analysis
Histograms, Bin Widths, and Cross Validation
Unequal n ANOVA and Types of Sums of Squares
Robustness of t test and ANOVA
Tags: software estatístico
R and the Nobel Prize API
Posted by Armando Brito Mendes | Filed under estatística, software, visualização
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Um bom exemplo do que se pode fazer com o R e uma API q serviços de dados.
he Nobel Prizes. Love them? Hate them? Are they still relevant, meaningful? Go on admit it, you always imagined you would win one day.
Whatever you think of them, the 2015 results are in. What’s more, the good people of the Nobel Foundation offer us free access to data via an API. I’ve published a document over at RPubs, showing some of the ways to access and analyse their data using R. Just to get you started:
Tags: análise de dados, belo, data mining, Estat Descritiva, R-software
KNIME Community Contributions
Posted by Armando Brito Mendes | Filed under materiais para profissionais, software
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Boa fonte de novos nós do KNIME, evitando q estejamos a programar algo q já foi programado antes.
KNIME Community Contributions offer a wide range of KNIME nodes from different application areas, such as chemo- and bioinformatics, image processing, or information retrieval. In contrast to the extensions available via the standard KNIME Update Site they are provided and maintained by various community developers.
The Trusted Community Contributions can easily be installed by selecting File -> Install KNIME Extensions in KNIME. Additional extensions are available by enabling the Update Site in KNIME via File -> Preferences -> Install/Update -> Available Update Sites. See the update site guide for details.
You can also download the whole update site as a ZIP archive and add the ZIP to the Available Update Sites (see above).
Tags: data mining, Knime, software estatístico, text mining
KNIME Update Site
Posted by Armando Brito Mendes | Filed under materiais ensino, software
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Formas alternativas de instalar novos nós no KNIME
Download KNIME Features using the KNIME Update Site
Additional KNIME plug-ins can be obtained via the KNIME update site which contains additional nodes/functionality for the KNIME workbench:
http://update.knime.org/analytics-platform/2.12/
Alternatively, the KNIME update sites can be downloaded as a zip file:
The KNIME Analytics Platform as well as all other KNIME products are linked automatically to the KNIME Update Site through the File menu via the “Install KNIME Extensions” command. We recommend using this command to access the KNIME Update Site.
If you are using KNIME SDK, a pre-existing Eclipse installation, or are working in an environment with limited internet access, another option for installing KNIME extensions is available. To access this additional dialog use the Help -> Install New Software command. This tool has a different interface that allows update sites to be manually specified. Clicking on “Add…” button (illustrated below) will allow you to either manually specify the url of the KNIME Update Site or use the offline (.zip) version of the Update Site to customize your KNIME installation.
Note: It is important not to unzip the archived KNIME Update Site file prior to specifying it as an update source for KNIME.
Tags: data mining, Knime
R news and tutorials R bloggers
Posted by Armando Brito Mendes | Filed under estatística, matemática, software
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Montes de blogs sobre R.
Here you will find daily news and tutorials about R, contributed by over 573 bloggers.
Top 3 Posts from the past 2 days
Top 9 articles of the week
- Installing R packages
- In-depth introduction to machine learning in 15 hours of expert videos
- New Version of RStudio (v0.99) Available Now
- Using apply, sapply, lapply in R
- Review of ‘Advanced R’ by Hadley Wickham
- Scatterplots
- An R Enthusiast Goes Pythonic!
- Open data sets you can use with R
- Basics of Histograms
Tags: R-software
S-PLUS & R Class Links
Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, materiais para profissionais, software
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montes de materiais para R e S-PLUS.
S-PLUS & R Class Links
Instructor: Richard Herrington
Why Do We Care To Use the “S” Language? Does anyone care besides us? The Association for Computing Machinery (ACM) cares
S-Plus
- Introduction to S language (S-Plus, R)
- S-Plus Windows Notes (MASS – Brian Ripley)
- S-Plus 6 Users Guide
- S-Plus 6 Users Guide to “Introduction to the Practice of Statistics”
- Datasets for “Introduction to the Practice of Statistics”
- S-Plus Tutorial
- S-Plus Website
- S-Plus Official Documentation
S-PLUS Student Edition Download (Free)
- Student Edition 6.2 – This version of S-Plus has a 20,000 cell or 1,000 row limitation; is only for educational use; is good for only one year; and is a rather large download (100+ meg).
S-PLUS Free Experimental Libraries and User Contributed Libraries
- Research Libraries – Includes: S+CorrelatedData (mixed effects generalized linear models), S+Best (B-Spline methods), S+Resample (bootstrap library), S+Bayes (bayesian analysis), S+FDA (functional data analysis).
- User Contributed Libraries
Tinn-R Script Editor
- SourceForge Download Site – Download Tinn-R Setup Files; Tinn-R can serve as a script editor and “pager” for R Console. See Tinn-R Convenient Script Editor for R on Win32 Platform
R
Download Site for the Current Windows Install Binary and R Packages
- Main CRAN Website
- CRAN Windows Binary – Installer for Win32 (also available for MacOS X and Linux
- CRAN R Package Descriptions – Pdf manuals available for packages
- R Packages Organized by Topic – Organized by discipline and methodology
Web Interfaces to R Web Servers and Example R Scripts
- R Web Interfaces – Web/browser based interfaces to R script processing on a server
- Example R Scripts – Some of these scripts run on a server and results are communicated thru a web browser
- RSS Rweb Server – Link to http:/rss.acs.unt.edu R server
R, R(D)COM and Excel
- Introduction to R – ppt
- Using R with Excel – A (D)COM Server for the Windows Platform – Benchmarks article (needs updating badly – Rich)
- R(D)COM Server Homepage – Thomas Baier
- R(D)COM Listserve Archive
- Download for single install file – R-2.4.1, R(D)COM and RExcel only
- Download for single install file – R-2.4.1 – use this file for a comprehensive install of selectable components: R, Rcmdr, R(D)COM, RExcel, rcom, gobbi, Rgobbi, and Tinn-R. R Version 2.5.0 combined install found here.
- Installing The R(D)COM server – Help Pages
- Using The R(D)COM server – Help Pages
- Using R Within Excel – Help Pages
- Duncan Temple Lang’s R (D)COM Homepage
- Duncan Temple Lang’s R (D)COM Notes
- Duncan Temple Lang’s R (D)COM Client examples– directory listing
- Duncan Temple Lang’s R (D)COM Server – examples listing
- General Computing Considerations
Tags: Excel, R-software, software estatístico
