Salford Predictive Modeller

Free Webinar Series - Data Science 101:
Learn How To Make Machine Learning Work

Machine learning may sound like an overwhelmingly complicated concept rather than a data-driven method to extract insights that drive future business decisions. To fully utilize machine learning, we first need to understand the benefits to our organization, and the techniques to create models based on questions we need to answer. 

In this ON-DEMAND webinar series, we will show you how to easily and automatically apply complex algorithms to data in real world applications.

In this webinar series you will learn:

  • Beginners will learn the basics. Data Science techniques that encompass the foundation of data modeling— key methods, building a predictive model, extracting value from complex datasets.
  • Advanced Modelers will continue to evolve their ability to leverage the power of data science. Improve both regression and classification models by utilizing automated features that shorten the time to create an accurate model.  We also cover how to better handle missing data, outliers, significant interrelationships among variables that are otherwise hard to capture.


Mikhail Golovnya, Senior Advisory Data Scientist, Salford Systems

Mikhail Golovnya has been prototyping new machine learning algorithms and modeling automation for the past 20 years. He has been a major contributor to Salford’s on-going search for technological improvements to among the most important algorithms in Machine Learning: CART® Decision Trees, MARS® Non-linear Regression, TreeNet® gradient boosting, and Random Forests®. Mikhail currently serves in the role of Senior Advisory Data Scientist and is leading the next generation of Salford Systems product development.

Charles Harrison, Marketing Statistician, Salford Systems

Charlie's statistical modeling background and knowledge of tree-based machine learning comes into play every day as he aims to make the most complicated algorithms easy for anyone to understand and use on their real-world data. While still in college, Charlie gained practical work experience by building sales forecasting models for the Advanced Analytics team at the J.M. Smucker Company and writing advanced Transact-SQL scripts as an intern on the network Analytics and Forecasting team at the Sprint Corporation.

We can help you harness the power of your data and transform it into insights you can act on.

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Salford Predictive Modeler.
Minitab's Integrated Suite of Machine Learning Software

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