The machine learning school 2010 conducted in Bangalore,India appears to be a success. The proceedings are now made available.
Download:
Associative Rule Mining
Graphical Models 1
Graphical Models 2
Graphical Models 3
Gaussian Processes
ML Introduction
Privacy Preserving Mining
Support Vector Machines
Machine Learning Summer School 2010’ will be hosted from June 14 – 19, 2010 at IISc Bangalore, from Yahoo! India Research & Development, in partnership with the Indian Institute of Science (IISc) Bangalore. This summer school is targeted towards academia as well as industry with a focus to deliver practical learning with or without machine learning exposure.
Schedule:
| Jun-14 (morning) | Nando De Freitas/Alex Smola Introduction to ML/Graphical Models |
| Jun-14 (afternoon) | Nando De Freitas Gaussian Processes |
| Jun-15 (morning) | Chiru Bhattacharyya Support Vector Machines |
| Jun-15 (afternoon) | Alex Smola Graphical Models and Kernels |
| Jun-16 (morning) | Jayant Haritsa Association Rule Mining |
| Jun-16 (afternoon) | Chiru Bhattacharyya Kernel Methods |
| Jun-17 (morning) | Nando De Freitas Bayesian Optimization |
| Jun-17 (afternoon) | Jayant Haritsa Privacy Preserving Mining |
| Jun-18 (morning) | John Langford Transformation of learning problem |
| Jun-18 (afternoon) | John Langford Learning in contextual bandit settings |
| Jun-19 (morning) | Deepak Agarwal Recommender problems: matrix factorization |
| Jun-19 (afternoon) | Deepak Agarwal Recommender problems: multi-resolution models |
More details visit :http://bangalore.yahoo.com/labs/summerschool.html
Are you a stat’s fan?, then pick up your copy of SAS for free starting this fall at your university!
On-Demand for Academics is an online program for teaching and learning data management and analytics. It allows professors and students to use several applications, including SAS Enterprise Guide and SAS Enterprise Miner for free. More applications may be added in the near future. Is SAS Institue following in the foot steps of software giants?, its something which we should wait and watch!
This time we bring to you an online video tutorial on CS 229: Machine Learning course from Stanford University. Besides 19 Lectures on machine learning you will be provided with relevant lecture notes, links other related miscellaneous stuff . Professor Andrew Ng will introduce machine learning and statistical pattern recognition which will cover topics like supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Other applications of machine learning, such as to robotic control, data mining, autonomous navigation, bio informatics, speech recognition, and text and web data processing are also discussed.
This was the first lecture:- (course materials) The first 30 minutes or so of this lecture is introduction to the course and the field of machine learning in general.
In the second lecture, Professor Andrew Ng will cover topics like linear regression, gradient descent, and normal equations and discusses how they relate to machine learning.
For more visit the home page: http://cs229.stanford.edu/
DataMiningTools Blog
Loading ...