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!
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
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
hthttps://blog.stcloudstate.edu/ims?s=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
https://blog.stcloudstate.edu/ims?s=copyrig
hthttps://blog.stcloudstate.edu/ims?s=data+mining
Privacy in the Surveillance Age: How Librarians Can Fight Back.
Wednesday, December 9, 2015
2pm Eastern (11am Pacific | 12pm Mountain | 1pm Central)
Description:
In the wake of Edward Snowden’s revelations about NSA and FBI dragnet surveillance, many Americans are concerned that their rights to privacy and intellectual freedom are under threat. But librarians are perfectly positioned to help our communities develop strategies to protect themselves against unwanted surveillance. In this webinar, Alison Macrina and April Glaser of the Library Freedom Project will talk about the landscape of surveillance, the work of the LFP, and some tips and tools librarians can use to resist pervasive surveillance in the digital age.
About the Presenters:
Alison Macrina is a librarian, privacy rights activist, and the founder and director of the Library Freedom Project, an initiative which aims to make real the promise of intellectual freedom in libraries by teaching librarians and their local communities about surveillance threats, privacy rights and law, and privacy-protecting technology tools to help safeguard digital freedoms. Alison is passionate about connecting surveillance issues to larger global struggles for justice, demystifying privacy and security technologies for ordinary users, and resisting an internet controlled by a handful of intelligence agencies and giant multinational corporations. When she’s not doing any of that, she’s reading.
April Glaser is a writer and an activist with the Library Freedom Project. She currently works as a mobilization specialist at Greenpeace USA, where she focuses on ending oil extraction in the Arctic. Prior to Greenpeace, April was at the Electronic Frontier Foundation, organizing around the net neutrality campaign and EFF’s grassroots programming. April also previously worked with the Prometheus Radio Project, where her efforts helped propel the passage of the Local Community Radio Act, the largest expansion of community radio in U.S. history. She lives in Oakland, California and continues to work with local organizations on a range of digital rights issues.
Can’t make it to the live show? That’s okay. The session will be recorded and available on the Carterette Series Webinars site for later viewing.
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To register for the online event
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2. Complete and submit the form.
3. A URL for the event will be emailed to you immediately after registration.
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Contact a member of the Carterette Series planning team with questions or suggestions:
More on privacy in this IMS blog:
Digitization and Libraries
Thursday, September 10, 2015
2 PM Eastern | 1 PM Central
12 PM Mountain | 11 AM Pacific
Digitization is a rapidly growing area of librarianship. Whether you’re a community repository or you need to digitize old materials to save space, the ability to start a digitization project is becoming an essential skill for the modern librarian.
Join us for a new episode of American Libraries Live, Digitization and Libraries. Our expert panel will discuss digitization in both broad and specific terms, looking at current trends and long-term implications for the library community.
Our panel will include:
• Susanne Caro, Government Documents Librarian at University of Montana, author and frequent speaker on digitization and librarianship
• Alyce Scott, Professor, School of Library & Information Science San Jose State University
Tune in for this free, streaming video broadcast! You can pre-register here for this free event (pre-registration assures you a reminder before the event), or go to http://www.americanlibrarieslive.org on September 10 at 2:00 p.m. (Eastern) to view.
We are pleased to welcome the School of Information (iSchool) at San José State University as a sponsor for this episode. The iSchool prepares individuals for careers as information professionals. Graduates work in diverse areas of the information profession, such as user experience design, digital asset management, information architecture, electronic records management, information governance, digital preservation, and librarianship. Based in the heart of Silicon Valley, the iSchool is the best place to learn online.
The iSchool’s Master of Library and Information Science (MLIS) degree program was named Outstanding Online Program by the Online Learning Consortium. This prestigious national award recognizes the school’s commitment to delivering innovative, convenient, 100% online learning solutions for students across the globe. Find out more about the iSchool’s award-winning online educational programs at ischool.sjsu.edu.
