Viva La Data Revolution: Introduction to Tools & Algorithms in Data Science & Machine Learning
You will learn:
- How machine learning works and its applications
- Practical tips to start using machine learning models
- Machine Learning algorithms, including Decision Trees, K-Means, K-Nearest Neighbors, Linear Regression, and Naïve Bayes, and how and when to use them
- The terminology, uses, and conceptual methodology of many of the most common data science tools
- A variety of resources to start or continue developing a machine learning skillset
![author]()
Wes Womer
Transaction Advisory Services Manager
KSM
Wes started his career as a Finance Analyst at Johnson & Johnson and Body Shop of America before moving into a Financial Planning role at Stanley Black and Decker. After being exposed to the S&OP process, his introduction to demand panning had begun and he would spend the next 5 years as Stanley Black and Decker’s S&OP/Sales Forecasting Manager. Wes is now Senior Finance Manager, Pricing Market and Analytics, at Wabash National, where he employs cutting edge machine learning and predictive analytics to drive forecasts and business insight. He holds a Law Degree from Indiana University, an Accounting degree from Butler University, a Master’s in law from The University of Alabama, and a Master of Science, Data Science, from India University.
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