Free make learning japanese software for linux

machine learning framework for Mathematica is a collection of powerful machine learning algorithms integrated into a framework for the main purpose of data analysis.
Fuzzy logic is one of its key techniques. The framework allows for combining different machine learning algorithms to solve one single problem. This combination of distinct algorithms may give the user unforeseen insights into its data.
The algorithms are highly parameterizable. Given this parameterizability combined with the efficient core engine of the machine learning framework for Mathematica, the user is able to analyze their data interactively, with short cycles of changing parameter settings and examining the results.
The machine learning framework for Mathematica covers a wide range of machine learning algorithms which can be integrated to work together and therefore yield new results.
Enhancements:
- runs native on Intel-Macs
- runs in 64-bit mode on G5-Macs
- fuzzy decision trees
- fuzzy rule learning
- fuzzy regression trees
- cluster descriptions
- optimization of fuzzy controllers
- self-organizing maps
- automated model testing
- advanced data visualization.

Klaid - K Learning Aid pops up kvtml file items on the desktop. Use KWordQuiz or FlashKard to produce kvtml files and load them into Klaid. It will grab all complete n x m related items (e.g. "Question" and "Answer", or "Word A" and "Word B") and displays them periodically as PopUps on the desktop. It is like someone is sitting behind you making sure you know all the terms for your next exam or test while surfing the web, coding, or whatever.
Intsllation:
Extract the archive, run "make -f Makefile.cvs && ./configure --prefix=PATH" first. Insert your KDE base installation dir for PATH. In Debian sid and Kubuntu that would be "/usr".
Then compile by typing "make". You may then install the program (as root) via checkinstall or "make install".
Enhancements:
- Version 0.7.6 beta
- Added dutch translation (thanks to Pieter Pareit), added slovenian translation (thanks to Jaka Kranjc), small bugfixes, source should now compile smoothly again

Russian Language Learning is a Java application that helps you to learn Russian using the Leitner system.

Memorizing words and phrases will not only be more efficient, but the system is a joy to use. Each card also has the phrase spoken by a native russian speaker, to help with pronunciation.

The Leitner system is a way of progressively learning words by placing them in stacks. The words you know are placed in stacks seperate from the words that are still troubling you, for more efficient learning.

And there is one other thing about Tanooshka.com language learning. Each set of cards, are the words to a movie, so when youve learned the set of words, you can watch the movie, and understand it! In Russian!

Bit-mapped Japanese font parser is a font parser. Note, this package doesnt include the actual font data. To get the font data you need to download it from the download section in the left.
Then move *.jfr into the directory where you unpacked this parser, and follow with the quick instructions.
Quick instructions:
Complete parse requires about 4 megabytes of free disk space. This is a huge improvement over the original version which required almost 45 megabytes.
1. make
2. make parse
3. watch the progress indicator
4. mv *.pcf.gz /usr/X11R/lib/X11R6/fonts/misc
5. make clean
6. HUP your font server if you use one
7. xset fp rehash
8. xlsfonts | grep kanji
/usr/X11R/lib/X11R6/fonts/misc is the standard location for all sorts of random bit-mapped fonts, but you might have a special location. Substitute that in step 4.
About:
I came across a number of these "raster fonts" a while ago. Quick look inside the files proved that they are bit-mapped fonts, and the format looked pretty straight-forward. I wrote the original parser for these just guessing the values, basically by experimenting and playing around. Later on I came across some docs on the subject - looks like these fonts were used in Windows 3.1 Japanese edition to substitute back-then low quality Japanese TTF fonts at small point sizes. These were designed using full-scale 16 bit programming techniques.
Quick info about the font format, there are some headers, then follows a "segment table" which is basically a table with pointers inside the font file where to locate a particular chunk of data. Because the 16 bit way of accessing memory is by using 65k "segments", each file is virtually split into < 65k segments which get loaded into separate memory areas, and then there is a algorithm how to assemble whatever character by using the segment number and offset. Anyway, with 32 bit access all of that doesnt really matter. In my implementation I just mmap the whole file and read it all out of memory.
Generating table.h was a LOT of work! First, I took the codearea table out of one of the jfr files (this maps shift-jis code to the character number inside the font file), and extracted the number ranges. These were shift-jis, of course, and X uses jis0208. There is no converter from a shift
jis byte into jis0208. So I had to write one. Taking iconv, and some tables from glibc 2.1.93, I hacked together something which converted the shift-jis data into ucs4 (unicode, I guess) and then from that into jis0208. The code to the converter is about 500k thanks to the huge jis->unicode->jis conversion tables, and you wont need it unless you get a jfr font with a different encoding table (unlikely). Anyway. After I got the font format figured out and converted the character table, everything else was pretty easy. Note some bit hackery in the bitmapXX() functions which was necessary to present the font data in a usable format. Also notice cool use of function pointers to select a conversion function at runtime.
Enhancements:
- This version uses correct JISX0208 tables, and is much faster.

OO Learning Evaluation GO is an object-oriented platform and algorithms for the game of GO.
It aims to provide a capable engine that can learn through experience and a re-usable algorithmic framework for the rapid development of new GO-playing engines.
Enhancements:
- Reorganization of the code was started so that various learnable evaluation functions can be used easily.
- Learning is currently tested in the GoPlayer module.
- The learned function simply learns to imitate the current static function.

Make-Debian-X11 is an add-on which makes a template with the necessary replacement files for gBootRoots Yard Method.

The root filesystem created from the template is user-mode-linux ready and includes X11, making it possible to run gBootRoot from within its own creation.

Japanese Flashcards is a set of flashcards for those learning Japanese. To use it scroll up to reveal the english translation. If you scroll back it will hide it and if you middle click a menu to change chapters will appear.

This theme is far from perfect. It will follows the vocabulary from the text book Nakama 1 by Seiichi Makino.