Saturday, December 8, 2018

Everything You Wanted to Know About Machine Learning....

...but didn't know whom to ask! Prof Sanjeev Arora, Princeton University, speaking at the Institute of Advanced Study

In a simple one-hour lecture (although one which does assume a certain amount of mathematical sophistication on the part of the audience, which, given that the audience consists mostly of mathematicians at the Institute of Advanced Study, is amply justified!), and one which already has had several thousands of views on youtube, Professor Arora describes the three main categories of Machine Learning Algorithms (Supervised, Unsupervised and Reinforcement Learning), and provides recent examples of 'successes' in each. Reinforcement Learning, which is taken up last, is nevertheless covered in sufficient detail, not leaving the viewer disappointed, and somewhat to one's  pleasant surprise as the lecture unfolds!

One of the topics taken up in some detail is the prediction of ratings for books based on the text of existing reviews, an application under the broad rubric of Natural Language Processing - and a subject of Prof. Arora's own recent work. The topic well illustrates many of the practical issues and methods involved in applications of machine learning, and also provides the intuition for developing theoretical ideas regarding how machine learning works. My own perspective is that of someone who knows much of the subject matter of the lecture for nearly three decades, since the mid-1980s, but I nevertheless found it a useful hour well-spent (on which, one might also add, that the lecture finishes almost exactly in an hour, showing also excellent time management on Prof Arora's part, as the lecture dynamically evolves!). What I greatly appreciated also was that Prof Arora reiterates several times during the talk the main reasons for the heightened interest in machine learning today, and this gives further insight into why someone - even if they might have been, for whatever reason (but especially out of an informed skepticism regarding such methods, as Prof Arora hints was the case with him) previously indifferent to the field - might now become interested, or even very interested in it. Another aspect of the lecture worth mentioning, especially these days when it is such a rarity, is that Prof Arora uses blackboard-and-chalk throughout - this added to my own enjoyment of the lecture, and doubtless also did the same for its live audience - a certain spontaneity is inevitably lost when lecturers use slides prepared earlier.

Two thumbs up, then!

Sunday, June 3, 2018

UK's NIESR Simulates Italy Near-term Macroeconomic Conditions




Friday, June 1, 2018

OECD Economics Projects India GDP Growth in 2019 at 7.5%





Thursday, May 31, 2018

Nearly a Quarter of American Adults are Unbanked or Underbanked!




The Federal Reserve's Survey of Household Economics and Decisionmaking (SHED)





Tuesday, May 29, 2018

GDP: An Incomplete and Imperfect Measure of Economic Activity






Sunday, May 27, 2018

Could Italy Exit the Eurozone, or even the European Union?





Friday, May 25, 2018

Is India's Economic Growth Slowing in the Most Labour-Intensive Sectors?






Sunday, May 13, 2018

How Europe too could be a Superpower, like China and the US!


Friday, May 11, 2018

The Natural Rate of Unemployment, Potential Output and Current GDP Trends




Tuesday, May 8, 2018

Geopolitical Risk, Demand-Supply Dynamics and the Oil Price Rise



Macroeconomic Impact of Recent Oil Price Rise



Sunday, May 6, 2018

India: Job Creation Statistics