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Data Science Central

Data Science Central

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Stay Connected to Your Future - Young African Leaders Initiative Network Spotlights and How-to Guides Every day, YALI Network members do extraordinary things. You can learn more about their achievements – and access practical information to help you achieve your own goals – on the YALI Network blog. There are more than 175 blog posts on the website with new ones published each week. These posts include everything from interviews with YALI Network members on farming and voter education to how-to guides on starting a business and making the most of your job search. Offline Connections We are almost there! Sorry for the long silence since my last post – we’ve been busy getting everything ready! We’re in fact almost there now and will be publishing our first articles in the next few days. As we announced back in January, we expect to publish a small number of articles over the coming months so that we can fully test the publishing model and tweak it as necessary before more formally launching towards the end of the year. In the meantime, here are a few updates ahead of these first articles:

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. There are far fewer resources out there about the steps to take in order to obtain the skills necessary to practice this elusive discipline. Introduction To Data Science Win-Vector LLC’s Nina Zumel and John Mount are proud to announce their new data science video course Introduction to Data Science is now available on Udemy. We designed the course as an introduction to an advanced topic. The course description is:

Explore the various types of marketing strategies used by professionals Exlore the strategies you will become familiar with as a professional marketer... Very often the success or failure of a company is a direct result of an effective or not so effective marketing strategy. Therefore, choosing a marketing strategy that fits the company product is of vital importance. Deciding on your audience The first step toward developing an appropriate marketing strategy is to know your audience. Are they 15 to 25 year old gamers? 21 to 40 year old football fans? Neanderthal sex debate highlights benefits of pre-publication An argument over sex that has been going on for more than a year is finally seeing the light of day. Today, scientists at the University of Cambridge, UK, and Harvard Medical School in Boston, Massachusetts, let the world in on a long-running discussion over whether or not humans and Neanderthals really interbred — and how you go about proving it. I’ll get to the sex. But this debate underscores a topic I wrote about last month (see ‘Geneticists eye the potential of ArXiv‘) that noted that high-profile papers from population geneticists are beginning to appear on the preprint server, once the domain just of theoretical physicists. That story is relevant because a new paper, entitled ‘The date of interbreeding between Neandertals and modern humans’, was posted to ArXiv on Friday. Meanwhile, a second paper raising doubts about human-Neanderthal hanky-panky appears in the Proceedings of the National Academy of Sciences (PNAS) today.

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: 1.

Data Cultivation - MonkeyFist Marketing Introducing the "Fox In The Hen House" Most marketing companies will tell you how important Database Collecting is to your business and how good they are at doing it. Well, MonkeyFist is not like most marketing companies. Top 40 Useful Sites To Learn New Skills The web is a powerful resource that can easily help you learn new skills. You just have to know where to look. Sure, you can use Google, Yahoo, or Bing to search for sites where you can learn new skills , but I figured I’d save you some time. The 1000 Genomes Project: data management and community access : Nature Methods High-throughput sequencing technologies, including those from Illumina, Roche Diagnostics (454) and Life Technologies (SOLiD), enable whole-genome sequencing at an unprecedented scale and at dramatically reduced costs over the gel capillary technology used in the human genome project. These technologies were at the heart of the decision in 2007 to launch the 1000 Genomes Project, an effort to comprehensively characterize human variation in multiple populations. In the pilot phase of the project, the data helped create an extensive population-scale view of human genetic variation1. The larger data volumes and shorter read lengths of high-throughput sequencing technologies created substantial new requirements for bioinformatics, analysis and data-distribution methods. The initial plan for the 1000 Genomes Project was to collect 2× whole genome coverage for 1,000 individuals, representing ~6 giga–base pairs of sequence per individual and ~6 tera–base pairs (Tbp) of sequence in total.

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. Finally, the idea of randomized node optimization, where the decision at each node is selected by a randomized procedure, rather than a deterministic optimization was first introduced by Dietterich.[7]

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