Hector Zenil. CS 188: Lectures. Features. Core KNIME features include: Scalability through sophisticated data handling (intelligent automatic caching of data in the background while maximizing throughput performance) High, simple extensibility via a well-defined API for plugin extensions Intuitive user interface Import/export of workflows (for exchanging with other KNIME users) Parallel execution on multi-core systems Command line version for "headless" batch executions Available KNIME modules cover a vast range of functionality, such as: retrieves data from files or data bases pre-processes your input data with filtering, group-by, pivoting, binning, normalization, aggregation, joining, sampling, partitioning, etc. visualize data and results through several interactive views, allowing for interactive data exploration ensures hilited data points in one view are also immediately hilited in all other views Supported Operating Systems Windows - 32bit (regularly tested on XP and Vista) Mac OSX - 64bit Intel-based architecture with Java 1.6 Read.
Shared notebook: Bayes' Theorem: Conditional Probabilities. You have been to this page before and wish to skip the preliminaries, click here to go directly to the computational portion of the page. For the application of Bayes' theorem to the situation where "probability" is defined as an index of subjective confidence, see the page Bayes' Theorem: "Adjustment of Subjective Confidence" . Bayes' theorem describes the relationships that exist within an array of simple and conditional probabilities.
For example: Suppose there is a certain disease randomly found in one- half of one percent (.005) of the general population. A certain clinical blood test is 99 percent (.99) effective in detecting the presence of this disease; that is, it will yield an accurate positive result in 99 percent of the cases where the disease is actually present. The probability that the disease will be present in any particular person the probability that the disease will not be present in any particular person P (B) = [ P (B|A) x P (A) ] + [ P (B|~A) x P (~A) ] Home. LarveCode. Principles of Artificial Intelligence: Study Guide. The material to be covered each week and the assigned readings (along with online lecture notes, if available) are included on this page. The study guide (including slides, notes, readings) will be updated each week.
The assigned readings are divided into required and recommended readings and notes from recitations (if available). You will be responsible for the material covered in the lectures and the assigned required readings. You are strongly encouraged to explore the recommended readings. Week 1 (starting August 23, 2009) Overview of the course; Overview of artificial intelligence: What is intelligence?
Required Readings -- Artificial Intelligence Required Readings -- Programming You may skip most of these readings if you have prior programming experience in Java. Getting Started with Java PDF Java for C++ Programmers by Marv Solomon, University of Wisconsin-Madison. Week 2, Starting Aug 30, 2009 Goal-Based Agents. Heuristic search. Required readings Recommended readings G. Week 5 Week 6. AIspace.
S Python Class - Google's Python Class - Google Code. Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections.
The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material. This material was created by Nick Parlante working in the engEDU group at Google. Tip: Check out the Python Google Code University Forum to ask and answer questions. Free Educational Video Tutorials on Computer Programming and More! » Python.
Easy AI with Python.
[1110.2216] The Generalized A* Architecture. HCE. Stanford AI - Unit One.