What is probabilistic programming?

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Uma nova forma de trabalhar com modelos Bayesianos!

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In this post, I introduce the emerging area of probabilistic programming, showing how probabilistic programs will hopefully make it easier to perform Bayesian-style machine learning, among other applications. Probabilistic programming is an exciting, and growing, area of research, with fantastic people in both AI/ML and PL working together and making big strides. PL methods — including formal semantics, optimization techniques, and forms of static analysis — have proven very useful in advancing this area forward.

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portal smart datacollective.com

Um portal de notícias sobre ciencia dos dados, big data, analytics

Um portal de notícias sobre ciencia dos dados, big data, analytics

SmartData Collective, an online community moderated by Social Media Today, provides enterprise leaders access to the latest trends in Business Intelligence and Data Management. Our innovative model serves as a platform for recognized, global experts to share their insights through peer contributions, custom content publishing and alignment with industry leaders. SmartData Collective is a key resource for executives who need to make informed data management decisions.

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introducing R to a non-programmer in one hour

Uma introdução muito rápida

Uma introdução muito rápida

Biostatistics PhD candidate Alyssa Frazee was tasked with teaching her sister, an undergraduate in sociology, how to use R. She had only one hour.

Once you load in a dataset, things start to get fun. We learned a whole bunch of stuff from this data frame, like how to do basic tabulations and calculate summary statistics, how to figure out if you have missing data, and how to fit a simple linear model. This part was pretty fun because my sister started leading the session: instead of me saying “I’m going to show you how to do this,” it was her asking “Hey, could we make a scatterplot?” or “Do you think we could put the best-fit line on that plot?” I was really glad this happened — I hope it meant she was engaged and enjoying herself!

This is the nice thing about R. There are so many built-in functions and packages that you can get something useful with a few lines of code, and you don’t really even have to know what a function is to get started (although you should eventually). Then you can go as far down the rabbit hole as you want.

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Machine Learning MOOC

Um curso muito completo de machine learning

Um curso muito completo de machine learning

About the Course

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you’ll learn about some of Silicon Valley’s best practices in innovation as it pertains to machine learning and AI.

This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

FAQ

  • What is the format of the class?The class will consist of lecture videos, which are broken into small chunks, usually between eight and twelve minutes each. Some of these may contain integrated quiz questions. There will also be standalone quizzes that are not part of video lectures, and programming assignments.
  • How much programming background is needed for the course?The course includes programming assignments and some programming background will be helpful.
  • Do I need to buy a textbook for the course?No, it is self-contained.
  • Will I get a statement of accomplishment after completing this class?Yes. Students who successfully complete the class will receive a statement of accomplishment signed by the instructor.

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Medical Algorithms

Site com centenas de algoritmos usados em apoio à decisão médica

Site com centenas de algoritmos usados em apoio à decisão médica

Medal.org Limited owns and operates the largest international web-based knowledge base of medical algorithms and computational procedures for medical treatment and administration. Medal.org is the largest provider of medical algorithms and the biggest player in the medical algorithms market, with a background of 5 years of building up its internet presence, book series, and professional sponsorship.

Contents by Speciality

OnLine Calculators

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Academic Earth

Site com lições em vídeo

Site com lições em vídeo

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ACM SIGKDD Webcasts

Ficheiros de som com explicações sobre data mining

Ficheiros de som com explicações sobre data mining

A Tutorial on Learning Causal Influences

Exploring the Power of Links in Data Mining

Mining High-Throughput Biological Data

Towards Web-Scale Information Extraction

Web Content Mining

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Bioconductor

logo_bioconductorBioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, more than 400 packages, and an active user community.

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MC Genomics

BMC GenomicsBMC Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of genome-scale analysis, functional genomics, and proteomics. BMC Genomics (ISSN 1471-2164) is indexed/tracked/covered by PubMed, MEDLINE, BIOSIS, CAS, EMBASE, Scopus, Zoological Record, CABI, Thomson Reuters (ISI) and Google Scholar.

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