Coursera - Web Intelligence and Big Data

MP4 | AVC 74kbps | English | 960x540 | 30fps | 13h 33mins | AAC stereo 128kbps | 1.19 GB

Genre: Video Training

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.

Course Syllabus:

Introduction and Overview

Look: Search, Indexing and Memory

Listen: Streams, Information and Language, Analyzing Sentiment and Intent

Load: Databases and their Evolution, Big data Technology and Trends

Programming: Map-Reduce

Learn: Classification, Clustering, and Mining, Information Extraction

Connect: Reasoning: Logic and its Limits, Dealing with Uncertainty

Programming: Bayesian Inference for Medical Diagnostics

Predict: Forecasting, Neural Models, Deep Learning, and Research Topics

Data Analysis: Regression and Feature Selection