What’s New in KNIME Analytics Platform 3.6.
- KNIME Deep Learning
- Constant Value Column Filter
- Numeric Outliers
- Column Expressions
- Git Nodes
- Call Workflow (Table Based)
- KNIME Server Connection
- Text Processing
- Usability Improvements
- Connect/Unconnect nodes using keyboard shortcuts
- Replacing and connecting nodes with node drop
- Node repository search
- Usability improvements in the KNIME Explorer
- Performance: Column Store (Preview)
- Making views beautiful: CSS changes
- KNIME Big Data Extensions
- Create Local Big Data Environment
- KNIME H2O Sparkling Water Integration
- Support for Apache Spark v2.3
- Big Data File Handling Nodes (Parquet/ORC)
- Spark PCA
- Spark Pivot
- Frequent Item Sets and Association Rules
- Create Spark Context via Livy
- Database Integration
- Apache Kafka Integration
Management (Client Preferences)
- Job View (Preview)
- Distributed Executors (Preview)
General release notes
JSON Path library update
- Java Snippet Bundle Imports
I suspect it will be the KNIME Deep learning that will catch the eye, the ability to set up deep learning models using drag and drop. Use regular Tensorflow models within KNIME Analytics Platform and seamlessly convert from Keras to Tensorflow for efficient network execution
The new Create Local Big Data Environment node creates a fully functional local big data environment including Apache Spark, Apache Hive and HDFS. It allows you to try out the nodes of the KNIME Big Data Extensions without a Hadoop cluster.
The Knime blog has a post containing lots of user submitted tips and tricks
Ever sat next to a friend or colleague at the computer and were awed when you suddenly realised the way they do certain tasks is much better? We recently asked KNIME users to share their tips and tricks on using KNIME. In this series of posts we’ll be showing you how the experts use KNIME in the hopes that by sharing ideas you’ll discover some handy techniques.
Greg Landrum's ICCS 2018 presentation on slideshare
Don't forget to sign up for your chance to hear a webinar by Greg Landrum, Knime's VP for Life Sciences, this Wednesday, He will be talking about processing malaria HTS results using Knime and will give a tutorial on workflows developed for ligand-based virtual screening, based on results of a phenotypic HTS against malaria.
Wed, Feb 21, 2018 3:00 PM - 4:00 PM GMT
The MedChemWizard is a KNIME workflow designed to assist medicinal chemists with idea generation, ligand design and lead optimization using a number of common functional group transformations and medchem rules-of-thumb, this tutorial provided by Dr. Alastair Donald gives a detailed description of it's use.
KNIME 2.7 has been released.
KNIME now runs on Java 7 for Windows and Linux systems (Mac stays on Java 6) Eclipse update 3.7 increases stability on Mac and some Linux systems. BIRT 3.7 brings Open Office support among other new features
JFreeChart nodes have now more setting options in the “General Plot Options” tab of their configuration window.
In R-> Local there are a number of new nodes to import:
- “Table to R” can read a KNIME table into R and output the R workspace.
- “R to Table” takes an R workspace and outputs a KNIME table.
- “R +Data to R” takes an R workspace and optional data input and outputs an R workspace.
- “R to R-View” takes an R workspace and outputs a KNIME view
There is a KNIME tutorial here
The 1Q KNIME newsletter is out. Discussion of text mining, the Feb UGM and Tips and Tricks.
KNIME (Konstanz Information Miner) is a user-friendly and comprehensive open-source data integration, processing, analysis, and exploration platform.
There is a KNIME tutorial here.
From the KNIME newsletter
“…good news for our Mac Users! We have just released KNIME 2.5.4 which fixes issues caused by the latest Apple update of the Java environment. We are grateful to the very active KNIME community which has helped to identify and fix this problem.”
KNIME Desktop 2.5.4 can be downloaded from the download page (http://www.knime.org/download) or you can upgrade your existing KNIME installation by using the built-in update functionality available in the "File" menu
There is also a KNIME tutorial here