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Abhinav Upadhyay
Works at SocialTwist Inc.
Attended Northern India Engineering College, Lucknow
Lives in Hyderabad
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Abhinav Upadhyay

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+Coursera adds 17 new universities and 62 new courses. Complete list embedded in the post below

Courses will be added to Class Central ( shortly

Here's a list of 62 Coursera courses that were added today:

Exploring Quantum Physics
Animal Behaviour
Epigenetic Control of Gene Expression
Discrete Optimization
Principles of Macroeconomics
Software Defined Networking
The Modern and the Postmodern
Introduction to Systems Biology
Network Analysis in Systems Biology
Dynamical Modeling Methods for Systems Biology
Introduction to Tissue Engineering
Climate Change
Generating the Wealth of Nations
Exercise Physiology: Understanding the Athlete Within
Passion Driven Statistics
Introduction to Pharmacy
Principles of Public Health
Generation Rx: The Science Behind Prescription Drug Abuse
The Ancient Greeks
Modern European Mysticism and Psychological Thought
Synapses, Neurons and Brains
Coding the Matrix: Linear Algebra through Computer Science Applications
Introduction to Digital Sound Design
Immigration and U.S. Citizenship
The Language of Hollywood: Storytelling, Sound, and Color
The Fiction of Relationship
Science from Superheroes to Global Warming
Useful Genetics
Archaeology's Dirty Little Secrets
Introduction to Biology: DNA to Organisms
Science, Technology, and Society in China I: Basic Concepts
Sports and Society
The Science of Gastronomy
A New History for a New China, 1700-2000: New Data and New Methods, Part 1
Introduction to Improvisation
Introduction to Guitar
Property and Liability: An Introduction to Law and Economics
Introduction to Music Production
Linear and Discrete Optimization
Financial Engineering and Risk Management
Climate Literacy: Navigating Climate Conversations
Creative Programming for Digital Media & Mobile Apps
Malicious Software and its Underground Economy: Two Sides to Every Story
Introduction to Systematic Program Design
Pattern-Oriented Software Architectures for Concurrent and Networked Software
Nutrition, Health, and Lifestyle: Issues and Insights
Fundamentals of Human Nutrition
Global Sustainable Energy; Past, Present and Future
Global Health Cultures
How Music Works
Sustainable Agricultural / Urban Land Management
Data Management for Clinical Research
Why We Need Psychology
The Camera Never Lies
English Common Law: An Introduction
Online Games: Literature, New Media, and Narrative
Economic Issues Food & You
Today, we are thrilled to welcome 17 more universities — including four international schools — onto Coursera, including: • Berklee College of Music • Brown University • Columbia University • Emory......
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Abhinav Upadhyay

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The free book "Mining Of Massive Datasets" just added three new chapters:

Chapter 10. Analysis of Social Networks.

Chapter 11. Dimensionality Reduction.

Chapter 12. Large-Scale Machine Learning.
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Abhinav Upadhyay

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Some beaches in the Maldives appear to have shimmering water. The glow is caused by bioluminescence when a micro-organism in the water is disturbed by oxygen.

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Abhinav Upadhyay

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Representing words as high dimensional vectors

Making computers understand human language is an active area of research, called Natural Language Processing (NLP). A widely used method of NLP research involves the statistical modeling of N-grams (, which are collected from freely available text corpora, and treated as single “atomic” units. While this has the benefit of being able to create simple models that can be trained on large amounts of data, it suffers when a large dataset isn’t available, such as high quality transcribed speech data for automatic speech recognition, or when one wants to have a notion of similarities between words. 

In the paper Efficient Estimation of Word Representations in Vector Space (, Googlers Tomas Mikolov, +Kai Chen+Greg Corrado, and +Jeff Dean describe recent progress being made on the application of neural networks to understanding the human language. By representing words as high dimensional vectors, they design and train models for learning the meaning of words in an unsupervised manner from large textual corpora. In doing so, they find that similar words arrange themselves near each other in this high-dimensional vector space, allowing for interesting results to arise from mathematical operations on the word representations. For example, this method allows one to solve simple analogies by performing arithmetic on the word vectors and examining the nearest words in the vector space.

To get more information, and to get the open source toolkit for computing continuous distributed representations of words, aimed to promote research on how machine learning can apply to natural language problems, head over to the Google Open Source Blog, linked below. 
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Abhinav Upadhyay

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We are making freely available our upper-level programming languages course.  People anywhere are welcome to participate in this on-line version.  All the details are here:

Please feel free to disseminate this information.

I look forward to seeing you in class!

Shriram Krishnamurthi, Instructor
Joe Gibbs Politz, Associate Instructor

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Computer Science Nerd
Bragging rights
A GSoC'er
  • Northern India Engineering College, Lucknow
    Information Technology, 2007 - 2011
  • KV Gomti Nagar
    Mathematics, 2004 - 2006
Basic Information
Development Engineer @ SocialTwist Inc.
  • SocialTwist Inc.
    Development Engineer, 2012 - present
  • Ubuntu
    Volunteer Contributor, 2011 - 2011
  • Google
    Independent Contractor, 2011 - 2011
  • Hover Technologies
    Intern Developer, 2010 - 2010
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Lucknow - Barabanki