What is a ML platform?

A machine learning platform is for accelerating and automating the delivery lifecycle of predictive applications capable of processing big data using machine learning algorithms and similar techniques. A machine learning platform typically consists of two parts: one that offers developers a pre-trained model; and another that allows them to build machine learning models for their own data.

Softweb offers an open source ML platform that can be integrated with our IoT platform – IoTConnect. Our ML platform can also be used standalone for generating predictive models.

Our open Source ML Platform can be integrated with an IoT platform or can also be used stand-alone for generating predictive models. Our platform provides the following infrastructure to support your data analysis and modeling needs:

  • Connect

    Connect with engineering and business teams to explore data sources to find the right data from the right places in order to solve the current business problems. Provide your team with secure access to all the data in one place, so they can focus on analyzing the data, rather than working on how to access it. Provide access to your outputs and code to improve the visibility of your work and gain real value from it.

  • Iterate

    Deliver your best data science work in lesser time by setting up repeatable and standardized environments for team’s preferable open source tools. Our platform will allow your team to conduct analysis by coding in their favorite language and using their favorite code editor, which they can later run on the platform.

  • Reinforce

    Get insights from the collected data through reports and applications to spread knowledge across your organization. Creating and sharing data visualizations can allow your team members to analyze easily and make better decisions. Our ML platform also allows you to go through a list of machine learning algorithms and choose the one that caters your modeling needs.

  • Market

    Once you have the best-fitted algorithm, you can move from prototype to production by running your existing models as APIs or scheduled jobs. You can easily handle model management by testing multiple models at once, promoting new models into production, and iterating them over time.

Experiments

Machine learning makes way for limitless possibilities for businesses in different industry verticals. Here are just some of the ways in which we can help your business grow:

  • Predictive Maintenance
  • Social Media Analysis
  • Information Retrieval
  • Smart Factory
  • Telemetry Data Forecasting
  • Customer Segmentation
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Why organizations must implement machine learning

  • Blog

    Machine learning is incomplete without open source technology – Learn Why!

    Big players are giving away machine learning projects to the open source community

    Learn More

Features of ML Platform

  • Connect data from several data sources

    Our platform allows you to integrate it with 3rd party data sources. It accepts data from spreadsheets, databases, and CSV files, processes it, and provides visually rich analytics as output.

  • Integration with APIs and social media channels

    We allow integration of the platform with several freely available APIs and social media channels, which is beneficial in creating mobile applications and in responding to customer requests.

  • Data cleaning

    Our platform also handles the data cleansing process that can help you focus more on the areas where data is weak and need more attention.

  • Feature engineering

    The results you are going to achieve and the predictive models that are generated are directly related to the features in your data. The quantity and quality of the data features will decide whether your data model will be worthy or not.

  • Classification

    On the basis of the pre-trained data set and the categories in which its observations are classified, users can identify to which category the new set of data belongs, so as to identify the accuracy and the best suited algorithm for their data.

  • Regression

    The platform offers 7 state-of-the-art algorithms to help users in identifying the relationship among several variables. It also includes many techniques for analyzing and modeling of variables, when the relationship between a dependent variable and one or more independent variables are in focus.

  • Time Series Analysis

    The platform makes use of time series analysis to observe historical data and to forecast the behavior or pattern of the future data. This can be helpful in gaining insights and in forming future strategies.

  • Clustering

    Clustering allows the users to group tasks and objects in a way that objects of the same group are more similar to each other when compared to the objects of other groups.

  • Natural Language Processing

    If the platform truly understands both the content and context of the user, it gets much easier to derive efficient output from the gathered data. This can be achieved using natural language processing, which is used to train the data models on the ML platform.

  • Web Service Creation

    The ML platform that is integrated with the IoT platform can process and analyze data, and further use it to create web services, which can be deployed in real-time.

  • Image Processing

    We will provide the ability for Image Recognition and Image Segmentation where one can extract objects from within the image.

  • Cognitive Services

    Cognitive services that are a part of our ML platform provides real-time computing abilities to the end user, using which the system cannot only analyze the structured as well as unstructured data, but also learn from it over time.

Benefits of ML Platform

  • Integration with IoTConnect
  • Pre-trained models to showcase best suited algorithms
  • User management
  • Can be hosted on-premises or on cloud
  • Can be integrated with other 3rd party data sources and databases

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