Weka
Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. The videos for the courses are available on Youtube. An exciting and potentially far-reaching development in computer science is the invention and application of methods of machine learning (ML). These enable a computer program to automatically analyze a large body of data and decide what information is most relevant. This crystallized information can then be used to automatically make predictions or to help people make decisions faster.
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Coevera
4.8 out of 5 stars
(26 Ratings)
Coevera is an AI-native CRM and sales process platform for B2B sales organizations of 15 to 2,500 quota-carrying sellers — companies with a defined sales process, sales managers accountable for pipeline, and deals complex enough that consultation rather than transaction wins them. Formerly Pipeliner CRM, built since 2011 on one idea: a sales process should be visible, teachable and repeatable. Intelligence is the default state of the system, not a premium add-on. The platform is industry-agnostic; our strongest results have come from manufacturing, financial services, insurance, software, professional services, energy and mining.
Sales leaders buy Coevera for a forecast they can defend. Sales operations teams buy it because it can be configured, changed and reported on without a dedicated administrator, outside consultants or a multi-year build. Reps use it because the pipeline is visual and the next step is obvious.
• Voyager AI — predictive deal and pipeline guidance in context, with native MCP so Coevera data is available to the AI tools your team already uses.
• Visual pipeline management — drag-and-drop pipelines, buying centers and relationship maps, so who is involved in a deal and what stage it is actually in are both visible.
• Guided selling — your stages, required activities and qualification criteria enforced in the flow of work rather than in a document.
• Automatizer — no-code workflow automation your own ops team builds and changes.
• Reporting and forecasting built in — no BI license required, with BI Feeder exporting to Tableau, Power BI and others when your analysts want the raw data.
Three editions at three price points — $85, $115 and $150 per user per month. Implementations run in weeks, not quarters. Served markets: United States, Canada, the United Kingdom, Australia, New Zealand and Europe, with English, German, Spanish and Italian as focus languages.
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Vortini
Sales forecasting is always an important but challenging activity. This is, even more, the case when the business is experiencing change. Combine current pipeline details, historical analysis and behavior patterns to flag off-track forecasts and suggest a plan B. Mine your CRM for normally hidden deal data to construct a full history of forecasts, even if you haven’t kept them. Auto-populate your forecast with a recommended mix of deals based on current and historical deal data. Sales forecasts their next period, while Finance forecasts the next fiscal quarter and year. No need for dual forecasting systems. Sales isn’t just about the figure– you need analytics to understand and build on their potential to identify areas of under-performance and improve sales effectiveness. To thrive and succeed in today’s competitive environment you need to understand your customers, analyze their next move, and make the right offering.
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DataPreparator
DataPreparator is a free software tool designed to assist with common tasks of data preparation (or data preprocessing) in data analysis and data mining. DataPreparator can assist you with exploring and preparing data in various ways prior to data analysis or data mining. It includes operators for cleaning, discretization, numeration, scaling, attribute selection, missing values, outliers, statistics, visualization, balancing, sampling, row selection, and several other tasks. Data access from text files, relational databases, and Excel workbooks. Handling of large volumes of data (since data sets are not stored in the computer memory, with the exception of Excel workbooks and result sets of some databases where database drivers do not support data streaming). Stand alone tool, independent of any other tools. User friendly graphical user interface. Operator chaining to create sequences of preprocessing transformations (operator tree). Creating of model tree for test/execution data.
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