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Machine Learning Without Coding

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Machine Learning Without Coding

Course Overview

R and Python are some of the most popular tools in the Data Analytics Ecosystem. One of the biggest demerits in them is the need to know the language and script the analysis. While it has its advantages, it can be major roadblock for non-coders.

In the UI based tools there is SPSS, and SAS but being commercial and with significant license costs, learning then can be quite a challenge.

One of the leaders in workflow based tool for Analytics is KNIME. It’s a UI driven tool with a workflow where we have to draw the flow and intuitively it builds the analytics chain. And the best part is that its open source.

This 3-Day workshop will help practitioners who want to get introduced with Machine Learning and Data Analytics using KNIME.  This involves hands-on exercises with multiple techniques of analytics, advanced predictive concepts, multiple business scenarios and case studies to work on to ensure that participants familiarized with the discipline of business analytics.

This course is recommended for executives, managers, and professionals who are in keen to get into the field of analytics and would like to know the full chain involved.

 This includes:

  • Managers driving organizational initiatives
  • Six Sigma Professionals
  • Industry professionals
  • Information Management Specialists in the organization

Process and metrics specialists providing information and dashboards to executive management

The following are the topics that will be covered in the workshop:

  • Introduction to data analytics
    • Define Analytics and terms associated
    • Use cases of application of analytics
    • Analytics Lifecycle Using CRISP-DM Methodology
  • Introduction to business analytics
    • Define Analytics and terms associated
    • Use cases of application of analytics
    • Analytics Lifecycle Using CRISP-DM Methodology
  • Introducing KNIME – Open Source Workflow based Analytics tool
  • Data Cleaning and Pre-Processing using KNIME
  • Data Exploration using KNIME
  • Advanced Data Analysis and Interpretation with KNIME
    • Advanced Statistics and Interpretation in the business context KNIME
      • Linear Regression
      • Decision Trees
      • Random Forests
      • Boosting
      • Logistic regression
      • Clustering
      • Text Analytics
    • Summary
      • Demo of few other techniques
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Machine Learning Without Coding

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