Search Results for "work time"

Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) ...

...The simpler the class hierarchy, the easier solution; 2. The data structures tend to change over time, or not be known in advance, working with them must be maintained; 3. All routine work ETL should be automated wherever possible; 4. Compiling the code on the fly bail speed and reserve for the optimization; 5. Sophisticated class hierarchy guarantee easy connection of other open source solutions.

OpenUnderwriter is an open source software house specialising in the development of IT solutions for the insurance market. Specialists in the areas of eBusiness and component based development, the team has developed technology for a number of major insurance companies. The OpenUnderwriter platform has been collaboratively developed by some of the best technical brains in the Insurance Industry and offers a viable alternative to traditional solutions. To date, OpenUnderwriter has been...

Seldon Server is a machine learning platform and recommendation engine built on Kubernetes. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production. Seldon Core is a progression of the goals of the Seldon-Server project but also a more restricted focus to solving the final step in a machine learning project which is serving models in production. ...

Bias is a cross-platform versatile information management application / Organizer

Apache Kafka is a distributed streaming platform built around durable, partitioned logs called topics, enabling high-throughput, fault-tolerant event pipelines. Producers append records to partitions, brokers replicate them for durability, and consumer groups read them at their own pace while balancing work across instances. The commit/offset model and retention policies support patterns from real-time processing to event sourcing and audit trails. Exactly-once processing semantics, idempotent producers, and transactions help prevent duplicates across complex dataflows. Kafka Streams and Kafka Connect extend the core: Streams provides a library for stateful stream processing within applications, while Connect standardizes integration with external systems. ...