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Web Intelligence And Big Data Homework 6 5th

5 years, 4 months ago

Wow. I am so impressed by this course. Of the 11 Coursera classes and 1 edX course which I actively participated in so far (most of which were in Machine Learning, Artificial Intelligence, NLP, etc.), I think this one might be my favorite. Unlike some of the other courses from Stanford or Berkeley which cover similar subjects (and are great as well), this course takes a much more practical/applied approach and examines the technologies used to actually perform these techniques as well as give a great overview of current methods. Nowhere else would I learn as much about state of the art techniques like HTM. Nowhere else would I get to play around with data on web scale using techniques like Map-Reduce. Nowhere else could I get as complete of a picture of the current methods for having computers simulate intelligence, make deductions, run logic based systems, use collaborative filtering, perform pattern recognition, etc. To get the sam... Wow. I am so impressed by this course. Of the 11 Coursera classes and 1 edX course which I actively participated in so far (most of which were in Machine Learning, Artificial Intelligence, NLP, etc.), I think this one might be my favorite. Unlike some of the other courses from Stanford or Berkeley which cover similar subjects (and are great as well), this course takes a much more practical/applied approach and examines the technologies used to actually perform these techniques as well as give a great overview of current methods. Nowhere else would I learn as much about state of the art techniques like HTM. Nowhere else would I get to play around with data on web scale using techniques like Map-Reduce. Nowhere else could I get as complete of a picture of the current methods for having computers simulate intelligence, make deductions, run logic based systems, use collaborative filtering, perform pattern recognition, etc. To get the same value as this course gave, at the least I would have to take courses on Information Retrieval, Natural Language Processing, Machine Learning, Artificial Intelligence and then do the hard work of tying the different subjects together. Obviously I think that this class was amazing. The quizzes were good tests of if you had understood the content of the lectures. The homeworks were a little sporadic and seemed slightly poorly planned but they were challenging and most importantly, they actually taught you something rather than merely testing if you could parrot back what the lectures had just taught you. I had a feeling of accomplishment when I finally got my tf-idf calculation running in map-reduce format or when I implemented a Bayesian-net to play doctor at diagnosing disease. In terms of practical applications, this course blows every other course out of the water.

The past decade has witnessed the successful of application of many AI techniques used at `web-scale’, on what are popularly referred to as big data platforms based on the map-reduce parallel computing paradigm and associated technologies such as distributed file systems, no-SQL databases and stream computing engines. Online advertising, machine translation, natural language understanding, sentiment mining, personalized medicine, and national security are some examples of such AI-based web-intelligence applications that are already in the public eye. Others, though less apparent, impact the operations of large enterprises from sales and marketing to manufacturing and supply chains. In this course we explore some such applications, the AI/statistical techniques that make them possible, along with parallel implementations using map-reduce and related platforms.

This course was offered thrice during Fall 2012, Spring 2012 and Fall 2013; in Fall of both years it was also taken for credit at IIT Delhi and IIIT Delhi. During this period, I also wrote a book to elucidate the ideas discussed in the course at a 'popular' level:

The Intelligent Web: Search, Smart Algorithms and Big Data published by Oxford University Press, UK, in November 2013.

Now in this edition, the course is being offered in 'self-study' mode.

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