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    Modern Data Science: Best Practices for Predictive Analytics

    Data science and machine learning provides the basis for business growth, cost and risk reduction and even new business model creation. Implementing predictive analytics does present some challenges, however. The process can be complex, and it can be difcult to find data scientists and analysts with a mix of the right skillsets. A drag and drop, visual data science tool, exemplified by IBM SPSS Modeler, enables rapid creation of machine learning models while making it easy to collaborate with data science and analytics teams as a whole. In this paper, members of IT Central Station who use IBM SPSS Modeler share their experiences and ofer insights and recommended best practices for data science and machine learning.

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    A business guide to modern predictive analytics

    This guide will help your business perform the following actions: 1) Navigate the modern predictive analytics landscape; 2) Identify opportunities to grow and enhance your use of AI; 3) Empower both data science teams and business stakeholders to deliver value fast.

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    Speed time to better AI outcomes

    Accelerate data science and AI project delivery with IBM Watson Studio Premium for Cloud Pak for Data.

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    The Forrester Wave™: Multimodal Predictive Analytics And Machine Learning Solutions

    In our 24-criteria evaluation of multimodal predictive analytics and machine learning (PAML) providers, we identified the 13 most significant ones — Dataiku, Datawatch, FICO, IBM, KNIME, MathWorks, Microsoft, RapidMiner, Salford Systems (Minitab), SAP, SAS, TIBCO Software, and World Programming — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise application development and delivery (AD&D) leaders make the best choice.

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    OpenSource and IBM SPSS Modeler

    A successful data-driven organization has to provide the right tools for its data analysts, developers, and business endusers. Increasingly, this means leveraging open-source software. But for all their benefits, popular open-source data programs also come with potentially time-consuming drawbacks. This paper will discuss how to handle these drawbacks, and get the right data tools to the right people, by leveraging popular open source tools with IBM® SPSS® Modeler software.

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    The Future of AI is Flexible: IBM chief scientist Ruchir Puri on IBM Cloud Pak for Data

    Register now to watch IBM Research Chief Scientist Ruchir Puri and Watson's Betsy Schaefer talk about the new flexibility to deploy Watson anywhere -- on the IBM Cloud, or on third-party clouds or hybrid clouds. Learn how to get started, hear about the deployment experience, and see the most common patterns with which clients are succeeding. In addition, Ruchir will give you a sneak peak into the future of AI.

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    The Forrester New Wave™: Conversational Computing Platforms

    IBM Watson Assistant is named as a leader in conversational computing. It has become increasingly important for businesses to build engaging interactions that deliver value to their customers, and IBM is proud to offer technologies that help developers and enterprises enhance those experiences. The report evaluated the most significant conversational computing platforms, diving into each vendor’s current offering and strategy and including customer feedback. IBM was cited for its developer-friendly tools and enterprise expertise requirements, which give developers access to the tools and technologies they need, while providing industry and enterprise support for their businesses.

  • Logo: IBM

    The Forrester Wave™: Multimodal Predictive Analytics And Machine Learning Solutions

    In our 24-criteria evaluation of multimodal predictive analytics and machine learning (PAML) providers, we identified the 13 most significant ones — Dataiku, Datawatch, FICO, IBM, KNIME, MathWorks, Microsoft, RapidMiner, Salford Systems (Minitab), SAP, SAS, TIBCO Software, and World Programming — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise application development and delivery (AD&D) leaders make the best choice.

  • Logo: IBM

    Speed time to better AI outcomes

    Accelerate data science and AI project delivery with IBM Watson Studio Premium for Cloud Pak for Data.

  • Logo: IBM

    Manage AI, with trust and confidence in business outcomes

    IBM Watson OpenScale is an open platform that helps remove barriers to enterprise-scale AI.

  • Logo: IBM

    A business guide to modern predictive analytics

    This guide will help your business perform the following actions: 1) Navigate the modern predictive analytics landscape; 2) Identify opportunities to grow and enhance your use of AI; 3) Empower both data science teams and business stakeholders to deliver value fast.

  • Logo: IBM

    Six reasons to upgrade your data science: How to become an AI-powered enterprise by tapping IBM

    Data science and AI simplified for you. The maturity of AI and machine learning (ML) use has reached a point where businesses of all sizes are using the technology as key strategic technology enablers. As an analytic and data science professional, you’re in control. You can empower people in centers of excellence (COE) and line of business (LOB) to C-level executives with scalable insights with trust and transparency. Data Science competency is critical for your business to increase predictability, optimize operations and govern use of AI. To succeed, leaders of your organization must harness the power of machine and human intelligence—data, talent and tools—while extracting actionable insights faster than ever. However, you have to bring your AI and ML experimentation into production to drive results while tackling your data and talent challenges. The question is, how will you innovate and move your business forward while preparing your data and analytics practice to harness the power of AI?