Archive of ‘information technology’ category

American Internet slow

Why Is American Internet So Slow?

Antiquated phone networks and corporate monopolies do not produce fast Internet.

By Rick Paulas
https://psmag.com/why-is-american-internet-so-slow-98f4eeadb371#.q9v3rd42k

AT&T, Comcast, Verizon, and Time Warner have a “natural monopoly” since they’ve simply been at it the longest. While the Telecommunications Act of 1996 attempted to incentivize competition to upset these established businesses, it didn’t take into account the near impossibility of doing so. As Howard Zinn wrote in A People’s History of the United States, the Telecommunications Act of 1996 simply “enabled the handful of corporations dominating the airwaves to expand their power further.”

Chattanooga has somewhat famously installed its own. Santa Monica also has its own fiber network. The reason these communities have been successful is because they don’t look at these networks as a luxury, but as a mode of self sustainability.

The 19th century’s ghost towns exist because the gold ran out. The 21st century’s ghost towns might materialize because the Internet never showed up.

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more on Internet access in this IMS blog

http://blog.stcloudstate.edu/ims?s=internet+access

text and data mining

38 great resources for learning data mining concepts and techniques

http://www.rubedo.com.br/2016/08/38-great-resources-for-learning-data.html

Learn data mining languages: R, Python and SQL

W3Schools – Fantastic set of interactive tutorials for learning different languages. Their SQL tutorial is second to none. You’ll learn how to manipulate data in MySQL, SQL Server, Access, Oracle, Sybase, DB2 and other database systems.
Treasure Data – The best way to learn is to work towards a goal. That’s what this helpful blog series is all about. You’ll learn SQL from scratch by following along with a simple, but common, data analysis scenario.
10 Queries – This course is recommended for the intermediate SQL-er who wants to brush up on his/her skills. It’s a series of 10 challenges coupled with forums and external videos to help you improve your SQL knowledge and understanding of the underlying principles.
TryR – Created by Code School, this interactive online tutorial system is designed to step you through R for statistics and data modeling. As you work through their seven modules, you’ll earn badges to track your progress helping you to stay on track.
Leada – If you’re a complete R novice, try Lead’s introduction to R. In their 1 hour 30 min course, they’ll cover installation, basic usage, common functions, data structures, and data types. They’ll even set you up with your own development environment in RStudio.
Advanced R – Once you’ve mastered the basics of R, bookmark this page. It’s a fantastically comprehensive style guide to using R. We should all strive to write beautiful code, and this resource (based on Google’s R style guide) is your key to that ideal.
Swirl – Learn R in R – a radical idea certainly. But that’s exactly what Swirl does. They’ll interactively teach you how to program in R and do some basic data science at your own pace. Right in the R console.
Python for beginners – The Python website actually has a pretty comprehensive and easy-to-follow set of tutorials. You can learn everything from installation to complex analyzes. It also gives you access to the Python community, who will be happy to answer your questions.
PythonSpot – A complete list of Python tutorials to take you from zero to Python hero. There are tutorials for beginners, intermediate and advanced learners.
Read all about it: data mining books
Data Jujitsu: The Art of Turning Data into Product – This free book by DJ Patil gives you a brief introduction to the complexity of data problems and how to approach them. He gives nice, understandable examples that cover the most important thought processes of data mining. It’s a great book for beginners but still interesting to the data mining expert. Plus, it’s free!
Data Mining: Concepts and Techniques – The third (and most recent) edition will give you an understanding of the theory and practice of discovering patterns in large data sets. Each chapter is a stand-alone guide to a particular topic, making it a good resource if you’re not into reading in sequence or you want to know about a particular topic.
Mining of Massive Datasets – Based on the Stanford Computer Science course, this book is often sighted by data scientists as one of the most helpful resources around. It’s designed at the undergraduate level with no formal prerequisites. It’s the next best thing to actually going to Stanford!
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners – This book is a must read for anyone who needs to do applied data mining in a business setting (ie practically everyone). It’s a complete resource for anyone looking to cut through the Big Data hype and understand the real value of data mining. Pay particular attention to the section on how modeling can be applied to business decision making.
Data Smart: Using Data Science to Transform Information into Insight – The talented (and funny) John Foreman from MailChimp teaches you the “dark arts” of data science. He makes modern statistical methods and algorithms accessible and easy to implement.
Hadoop: The Definitive Guide – As a data scientist, you will undoubtedly be asked about Hadoop. So you’d better know how it works. This comprehensive guide will teach you how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. Make sure you get the most recent addition to keep up with this fast-changing service.
 Online learning: data mining webinars and courses
DataCamp – Learn data mining from the comfort of your home with DataCamp’s online courses. They have free courses on R, Statistics, Data Manipulation, Dynamic Reporting, Large Data Sets and much more.
Coursera – Coursera brings you all the best University courses straight to your computer. Their online classes will teach you the fundamentals of interpreting data, performing analyzes and communicating insights. They have topics for beginners and advanced learners in Data Analysis, Machine Learning, Probability and Statistics and more.
Udemy – With a range of free and pay for data mining courses, you’re sure to find something you like on Udemy no matter your level. There are 395 in the area of data mining! All their courses are uploaded by other Udemy users meaning quality can fluctuate so make sure you read the reviews.
CodeSchool – These courses are handily organized into “Paths” based on the technology you want to learn. You can do everything from build a foundation in Git to take control of a data layer in SQL. Their engaging online videos will take you step-by-step through each lesson and their challenges will let you practice what you’ve learned in a controlled environment.
Udacity – Master a new skill or programming language with Udacity’s unique series of online courses and projects. Each class is developed by a Silicon Valley tech giant, so you know what your learning will be directly applicable to the real world.
Treehouse – Learn from experts in web design, coding, business and more. The video tutorials from Treehouse will teach you the basics and their quizzes and coding challenges will ensure the information sticks. And their UI is pretty easy on the eyes.
Learn from the best: top data miners to follow
John Foreman – Chief Data Scientist at MailChimp and author of Data Smart, John is worth a follow for his witty yet poignant tweets on data science.
DJ Patil – Author and Chief Data Scientist at The White House OSTP, DJ tweets everything you’ve ever wanted to know about data in politics.
Nate Silver – He’s Editor-in-Chief of FiveThirtyEight, a blog that uses data to analyze news stories in Politics, Sports, and Current Events.
Andrew Ng – As the Chief Data Scientist at Baidu, Andrew is responsible for some of the most groundbreaking developments in Machine Learning and Data Science.
Bernard Marr – He might know pretty much everything there is to know about Big Data.
Gregory Piatetsky – He’s the author of popular data science blog KDNuggets, the leading newsletter on data mining and knowledge discovery.
Christian Rudder – As the Co-founder of OKCupid, Christian has access to one of the most unique datasets on the planet and he uses it to give fascinating insight into human nature, love, and relationships
Dean Abbott – He’s contributed to a number of data blogs and authored his own book on Applied Predictive Analytics. At the moment, Dean is Chief Data Scientist at SmarterHQ.
Practice what you’ve learned: data mining competitions
Kaggle – This is the ultimate data mining competition. The world’s biggest corporations offer big prizes for solving their toughest data problems.
Stack Overflow – The best way to learn is to teach. Stackoverflow offers the perfect forum for you to prove your data mining know-how by answering fellow enthusiast’s questions.
TunedIT – With a live leaderboard and interactive participation, TunedIT offers a great platform to flex your data mining muscles.
DrivenData – You can find a number of nonprofit data mining challenges on DataDriven. All of your mining efforts will go towards a good cause.
Quora – Another great site to answer questions on just about everything. There are plenty of curious data lovers on there asking for help with data mining and data science.
Meet your fellow data miner: social networks, groups and meetups
Reddit – Reddit is a forum for finding the latest articles on data mining and connecting with fellow data scientists. We recommend subscribing to r/dataminingr/dataisbeautiful,r/datasciencer/machinelearning and r/bigdata.
Facebook – As with many social media platforms, Facebook is a great place to meet and interact with people who have similar interests. There are a number of very active data mining groups you can join.
LinkedIn – If you’re looking for data mining experts in a particular field, look no further than LinkedIn. There are hundreds of data mining groups ranging from the generic to the hyper-specific. In short, there’s sure to be something for everyone.
Meetup – Want to meet your fellow data miners in person? Attend a meetup! Just search for data mining in your city and you’re sure to find an awesome group near you.
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8 fantastic examples of data storytelling

8 fantastic examples of data storytelling

Data storytelling is the realization of great data visualization. We’re seeing data that’s been analyzed well and presented in a way that someone who’s never even heard of data science can get it.

Google’s Cole Nussbaumer provides a friendly reminder of what data storytelling actually is, it’s straightforward, strategic, elegant, and simple.

 

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more on text and data mining in this IMS blog
hthttp://blog.stcloudstate.edu/ims?s=data+mining

European Commission and text and data mining

The EU just told data mining startups to take their business elsewhere

Lenard Koschwitz

By enabling the development and creation of big data for non-commercial use only, the European Commission has come up with a half-baked policy. Startups will be discouraged from mining in Europe and it will be impossible for companies to grow out of universities in the EU.

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more on copyright and text and data mining in this IMS blog
http://blog.stcloudstate.edu/ims?s=copyrig
hthttp://blog.stcloudstate.edu/ims?s=data+mining

your privacy and Google

How to see everything Google knows about you

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more on privacy in this IMS blog

http://blog.stcloudstate.edu/ims?s=privacy

hackers versus crackers: Guccifer

Hackers versus crackers

http://www.techrepublic.com/blog/it-security/hacker-vs-cracker/

http://www.pctools.com/security-news/crackers-and-hackers/

Federal court sentences original Guccifer

By Mark Rockwell Sep 02, 2016

https://fcw.com/articles/2016/09/02/guccifer-sentence-rockwell.aspx

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more in this blog on hackers and crackers

http://blog.stcloudstate.edu/ims?s=hackers

http://blog.stcloudstate.edu/ims?s=crackers

 

Alphabet Nest and Android

Alphabet is breaking up Nest, its standalone smart-home gadgets company, and moving Nest’s software group back into Google.

enerally speaking, Google has very limited interest in making hardware in the first place. The cost of building things is high, the margins are low, and Google’s real specialty is in web services like Gmail and search anyway.

Google started signaling that Android, the most popular operating system in the world, and Chrome OS, its more niche operating system for laptops, were going to get smashed together. The result, ideally, will be a version of Android that can extend its smartphone dominance to tablets and laptops…which is why Android 7.0, the most recent release, makes split-screen multitasking such a tentpole feature.

the real business opportunity for Google is to compel a broad range of companies to create gadgets and home appliances using its software. The hardware is secondary. In fact, building its own hardware can even work against Google: The more successful Google is at selling its own hardware, the less likely other hardware makers want to use its software, since they view Google as a competitor.

Putting all its efforts behind expanding and extending Android has made Google a top player in the smartphone market, even after its late start against Apple and the iPhone.

Finding and Using E-Government Tools and Resources

Librarianship in the Modern Era

Cutting the Red Tape: Finding and Using E-Government Tools and Resources
Diane Kovacs

4-week eCourse
Beginning Monday, September 12, 2016

E-government tools and resources bring many people to your library for such activities as filing and paying taxes online, locating Medicare/Medicaid providers and reviews, checking student loan status, tracking regulatory changes for industries, monitoring ongoing legislation as well as codified law and court rulings, and much more. This hands-on eCourse also explores the information published online by the U. S. federal government through the Government Printing Office and specific agencies and government branches.
Experienced online instructor and consultant Diane Kovacs covers the best sites to begin researching for government information in general and specifically for business, healthcare, genealogy, history, current government, legal, regulatory, taxes, retirement, insurance, and state and local government information.

GLOBAL COLLABORATION DAY SEPTEMBER 15TH

Students, teachers, and organizations will join together online to celebrate and demonstrate global collaboration on September 15, 2016. On Global Collaboration Day, educators and professionals from around the world will host connective projects and events and invite public participation. This event is brought to you by VIF International Education, Google for Education, iEARN-USA and Edmodo.

The primary goals of this 24-hour, worldwide event are to:

  • demonstrate the power of global connectivity in classrooms, schools, institutions of informal learning and universities around the world
  • introduce others to the collaborative tools, resources and projects that are available to educators today
  • to focus attention on the need for developing globally competent students and teachers throughout the world

Global Collaboration Day will take place on September 15 in participant time zones. Classrooms, schools, and organizations will design and host engaging online activities for others to join. Events will range from mystery location calls to professional development events to interviews with experts. All events will be collated in an online calendar viewable in participants’ individual time zones. Participants will be connected on Twitter via the hashtag #globaled16.

An optional new activity this year will be the Great Global Project Challenge. Between now and October 1, 2016, global educators will design collaborative projects using a variety of platforms in which other students and teachers may participate during the course of the 2016-2017 school year. The objective is to create and present as many globally connective projects for students and educators as possible. The final deadline for submissions into our project directory is October 1, but participants are also encouraged to do an introductory activity for their project on Global Collaboration Day as well.

Global Collaboration Day is a project of the Global Education Conference Network, a free online virtual conference that takes place every November during International Education Week. GCD, along with Global Education Day at ISTE and Global Leadership Week, are events designed to connect educators and keep global conversations going year round.

For more information about Global Collaboration Day, please visit our main web site. A digital flyer is also available for distribution.

Follow us on social media:

 

Help us spread the word. Here are some sample Tweets:

  • Join us for Global Collaboration Day! Details here: http://bit.ly/2016GCD #globaled16
  • YOUR ORG’S TWITTER HANDLE is pleased to partner with @GlobalEdCon and educators around the globe for Global Collaboration Day: http://bit.ly/2016GCD
  • Are you an education leader? Inspire global collaboration on Global Collaboration Day 9/15. http://bit.ly/2016GCD #globaled16
  • Learn more about participating in the Global Collaboration Day celebration: http://bit.ly/2016GCD #globaled16
  • Project hosts are sought for Global Collaboration Day. Details here: http://bit.ly/2016GCD #globaled16

 

Logos and Badges for Participants, Hosts, Partners and Sponsors are located here: http://bit.ly/gcdimages

Interested in serving as an outreach partner?


Send an email to Lucy Gray (lucy@globaledevents.com) indicating your interest. Include information on how you can help us get the word out to networks with 5000 members or more.

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