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DataKind

DataKind

http://www.datakind.org/

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The One-Stop Shop for Big Data Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this survey paper. Once you know what they are, how they work, what they do and where you can find them, my hope is you’ll have this blog post as a springboard to learn even more about data mining. What are we waiting for? Let’s get started! Here are the algorithms:

Unearthing Data to Unleash Impact: Using Unique Data Sources to Drive Change About Nick: Nick is the Data Science Manager at DataKind, an organization committed to harnessing the power of data science in the service of humanity. He loves empowering mission-driven organizations through data, and was previously a Data Scientist at the Center for Data Science and Public Policy and the Data Science for Social Good Fellowship. About Neal: Neal is Director of Social Impact at Tableau Software and Director of Tableau Foundation, which encourages the use of facts and analytical reasoning to solve the world’s problems. Neal has served in both private and nonprofit senior leadership positions at intersection of information technology and social change.

A Practical Intro to Data Science — Zipfian Academy - Data Science Bootcamp Are you a interested in taking a course with us? Learn more on our programs page or contact us. There are plenty of articles and discussions on the web about what data science is, what qualities define a data scientist, how to nurture them, and how you should position yourself to be a competitive applicant. New Tool Puts Dollar Value on Social Projects Measuring the social impact of building low-cost housing, child-care centers, and health clinics in poor neighborhoods isn’t easy. But a new online tool takes a stab at putting a dollar value on such building projects, based on the best available social-science research. The Social Impact Calculator is the result of the Low Income Investment Fund’s effort to measure the effect of its own work. The fund couldn’t afford to do long-term studies on the people whose lives have been touched by the apartment buildings, schools, and clinics it finances. So the group sought out high-quality research that allows it to estimate a monetary value, says Nancy O. Andrews, chief executive of the Low Income Investment Fund.

Data journalism at the Guardian: what is it and how do we do it? Data journalism. What is it and how is it changing? Photograph: Alamy Random forest The selection of a random subset of features is an example of the random subspace method, which, in Ho's formulation, is a way to implement classification proposed by Eugene Kleinberg.[6] History[edit] The early development of random forests was influenced by the work of Amit and Geman[5] which introduced the idea of searching over a random subset of the available decisions when splitting a node, in the context of growing a single tree. The idea of random subspace selection from Ho[4] was also influential in the design of random forests. In this method a forest of trees is grown, and variation among the trees is introduced by projecting the training data into a randomly chosen subspace before fitting each tree.

The Chan Zuckerberg Initiative is Disrupting Nonprofits, And That’s a Good Thing (Photo Credit: istockphoto) *This article originally appeared in The Huffington Post. Jon Brilliant is co-founder and chief financial officer of BigfootBiomedical.com, a company that is changing the paradigm of care for Type 1 diabetes through the creation of a service-based durable business model that includes the automated delivery of insulin. Heat map Heat map generated from DNA microarray data reflecting gene expression values in several conditions Heat maps originated in 2D displays of the values in a data matrix. Larger values were represented by small dark gray or black squares (pixels) and smaller values by lighter squares.

Accelerating Social Impact CCC Pollster Doug Miller in his recently published book, “Can the World be Wrong?” predicts social enterprise ‘as the next big thing’ as we face “the ever-increasing pressure on business to act better in society’s interest…”[1] His prediction just might be confirmed by the amazing shifts and developments in the social enterprise arena across Canada in 2015. We have witnessed public policy changes, market growth, increased social impact reporting and emerging new partnerships all contributed to a more vibrant social enterprise sector. Some of what we’ve witnessed in 2015…

Starting Your Big Data Lab for a POC In continuation of my previous blog post, “6 Steps to Start Your Big Data Journey,” I want to address here the question “How should you start your big data journey?” What is the Big Data Lab? The Big Data Lab is a dedicated development environment, within your current technology infrastructure, that can be created explicitly for experimentation with emerging technologies and approaches to big data and analytics. Should foundations be playing a greater role in social investment? Just when you think you have dealt with one issue, for example, the availability of regular loans to charities, through Charity Bank, up pops another challenge – what about smaller, unsecured loans? Just when we’ve done that, through the Social Investment Business (SIB) and CAF Venturesome, along come charities and social enterprises asking “What about some finance involving equity, where I only start repaying you when the income stream we grow is up and running?” A raft of social enterprise venture funds later, along come community groups looking to raise community shares. So how do we support that?

Fall 10 Course: Introduction to Data Mining and Analysis Syllabus (tentative) What's this course about? Data is everywhere now, and advanced data analysis methods (variously called "machine learning", "data mining", and "pattern recognition") are now in use everywhere.

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