Download JAR files tagged by hand with all dependencies

ABBYY Cloud OCR SDK allows to recognize printed text (OCR) and hand-printed text (ICR) on images, convert image-only documents to searchable PDF or editable Microsoft Office formats, extract data from receipts, business cards and IDs through the simple HTTP API. This Java library provides classes and methods to access ABBYY Cloud OCR SDK API endpoints.

The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners.

JNAerator (pronounce "generator") simply parses C and Objective-C headers and generates the corresponding JNA and Rococoa Java interfaces (it also has a very limited support for C++). This lets Java programmers access native libraries transparently, with full IDE support and little to no hand-tweaking. Users who are looking for ready-to-use libraries should check the NativeLibs4Java project instead.

The ServiceMix Bean component provides integration with beans (POJOs) with the JBI bus to make it easy to use POJOs to process JBI message exchanges. Like in an Message Driven Bean in J2EE a POJO will receive a message from the NMR and process it in any way it likes. Unlike in a JMS component where the coding is already done the Bean component gives the developer the freedom to create any type of message handling but it must be hand coded all the way.

Maximum Likelihood Rule Ensembles (MLRules) is a new rule induction algorithm for solving classification problems via probability estimation. The ensemble is built using boosting, by greedily minimizing the negative loglikelihood which results in estimating the class conditional probability distribution. The main advantage of decision rules is their simplicity and comprehensibility: they are logical statements of the form "if condition then decision", which is probably the easiest form of model to interpret. On the other hand, by exploiting a powerful statistical technique to induce the rules, the final ensemble has very high prediction accuracy. Fork of the original code located at: http://www.cs.put.poznan.pl/wkotlowski/software-mlrules.html

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.