Machine Learning – A Few Links and Tweets

On Machine Learning from A free book on ML – A First Encounter of Machine Learning by Max Welling

The first reason for the recent successes of machine learning and the growth of the field as a whole is rooted in its multidisciplinary character. Machine learning emerged from AI but quickly incorporated ideas from fields as diverse as statistics, probability, computer science, information theory, convex optimization, control theory, cognitive science, theoretical neuroscience, physics and more.
The second, perhaps more important reason for the growth of m
achine learning is the exponential growth of both available data and computer power. While the field is build on theory and tools developed statistics machine learning recognizes that the most exiting progress can be made to leverage the enormous flood of data that is generated each year by satellites, sky observatories, particle accelerators, the human genome project, banks, the stock market, the army, seismic measurements, the internet, video, scanned text and so on.

On why this book was written

Much of machine learning is built upon concepts from mathematics such as partial derivatives, eigenvalue decompositions, multivariate probability densities and so on. I quickly found that these concepts could not be taken for granted at an undergraduate level.

Machine learning will be one of the most important tech trends over the next three to five years for innovation” http://t.co/kBFPHlANHa

Startups making machine learning an elementary affair http://t.co/FkF7TSy45R

Use Cases Machine Learning on Big Data for Predictive Analytics http://t.co/1AvQHXkgr4 #ml usecases

A startup journey, the improvement in Python’s data science capabilities and hosted machine learning http://t.co/Vx4g7lIM1X #techtrends

RT @woycheck: Zico Kolter wants to use machine learning to analyze electrical current behavior and provide details about your power bill (@…

Microsoft Research Machine Learning Summit: April 22-24, 2013 http://t.co/x9YxylgMeX

RT @siah: A free ebook by Max Welling “A First Encounter with Machine Learning” http://t.co/5KjCCylL3Y

Google Hires Brains that Helped Supercharge Machine Learning | Wired Enterprise | http://t.co/cVgZpNri4c http://t.co/2mJ7ggZE2n

RT @siah: PyMADlib: A Python wrapper for MADlib – an open source library for scalable in-database machine learning algorithms http://t.c

Peekaboo: Machine Learning Cheat Sheet (for scikit-learn) http://t.co/6UyYWO74

Panels and Discussions

This is a panel from Churchill Club featuring
Peter Norvig, Director of Research, Google ,Gurjeet Singh, Co-founder & CEO, Ayasdi, Jeremy Howard, President and Chief Scientist, Kaggle

Meta

Once in a while, I go and gather my recent tweets and create a Tweet Cloud (a project developed by a student). I find some interesting topics, save the tweets and start a blog. I have written about this Linked Tweet Cloud a couple of times.

tweets_on_machine_learning

LinkLog: The Architecture of Serendipity

One of the best chapters I have read in Where Good Ideas Come From by Steven Johnson,  is  “Serendipity”. Here are a few snippets:

The English language is blessed with a wonderful word that captures the power of accidental connection: “serendipity”

Serendipitous discoveries often involve exchanges across traditional disciplines.

The history of innovation is replete with stories of good ideas that occurred to people while they were out for a stroll.

The shower or stroll removes you from the task-based focus of modern life – paying bills, answering email, helping kids with homework – and deposits you in a more associative state. Given enough time, your mind will often stumble across some old connection that it had long overlooked, and you experience that delightful feeling of private serendipity: Why didn’t I think of that before?

While the creative walk can produce new serendipitous combinations of existing ideas in our heads, we can cultivate serendipity in they way that we absorb new ideas from the outside world. Reading remains an unsurpassed vehicle for the transmission of interesting new ideas and perspectives.

The problem with assimilating new ideas at the fringes of your daily routine is that the potential combinations are limited by the reach of your memory.

He talks about the web

No medium in history has ever offered such unlikely trails of connections and chance in such an intuitive and accessible form.

If the architecture of serendipity lies in stumbling across surprising connections while scanning the front page (of a news paper), then the web is more than 10 times as serendipitous as the classing print newspaper.

There can be little doubt that the web is an unrivaled medium for serendipity if you are actively seeking it out.

I do not want to clutter these gems with my thoughts. But after finishing this chapter, I went on a random walk into Wikipedia with some surprising discoveries.

This book is worth buying and reading just for this chapter alone. It is not only thought provoking but extremely inspiring as well.

LinkLog: Numerati, Semantics in Spreadsheets and the Future of Web Apps

InfoMinder Alerts on 21st Oct 08:

Steven Baker’s Numerati

A captivating look at how a global math elite is predicting and altering our behavior — at work, at the mall, and in bed

In this tour de force of original reporting and analysis, journalist Stephen Baker provides us with a fascinating guide to the world we’re all entering — and to the people controlling that world. The Numerati have infiltrated every realm of human affairs, profiling us as workers, shoppers, patients, voters, potential terrorists — and lovers. The implications are vast.

How Semantics Can Revolutionize Spreadsheets

Last fall, senior enterprise architect Brand Niemann of the Environmental Protection Agency issued a challenge to the semantic web industry: Who will step forward and show how to take the reams of government data currently locked away in spreadsheets to the semantic web? This spring, at the Semantic Technology Conference, May 18-22 in San Jose, Calif., Niemann and Lee Feigenbaum, VP technology and standards at Cambridge Semantics Inc., will demo the solution to that question.

What makes the spreadsheet such an important application to semantify? Put it down to a couple of things. The first is that lots of government data is stored in spreadsheets, inaccessible to the Google crawlers of the world. …This technology means they can continue using and working in the application they love, but develop semantic web applications at the same time.

Videos from the Future of Web Apps Conference

I just started watching  them.  Kathy Sierra’s is really good.

Language – Not Just the Transfer of Ideas

About Semantics from The Stuff of Thought by Steven Pinker

Semantics is about the relation of words to thoughts, but it is also the about the relation of words to other human concerns. Semantics is about the relation of words to reality – the way that speakers commit to a shared understanding of the truth, and the way their thoughts are anchored to things and situations in the world. It is about the relation of words to a community – how a new word, which arises in the act of creation by a single speaker, comes to evoke the same idea in the rest of the population so people can understand one another when they use it. It is about the relation of words to emotions: the way in which words just point to things but are saturated with feelings, which can endow the words with a sense of magic, taboo, and sin. And it is about the words and social relations – how people use language not just to transfer ideas from head to head but to negotiate the kind of relationship they wish to have with their conversational partner.