Machine Learning With R and Python
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Analytics uses the semantics of data to find meaningful patterns and knowledge and predict future trends. Machine learning applies these concepts to large sets of data associated with customers, business processes, and market economics. Machine learning applications are found in almost all industries. The success of today’s enterprises depends largely on their professionals’ ability to make faster and more accurate decisions to solve complicated business problems.
This program covers the underlying principles related to a wide variety of machine learning methods and algorithms plus the various procedures used to assess their validity in different applications. Participants will apply machine learning languages R and Python to select, build and use predictive models.
Data visualization enables the trends and patterns to be examined and assessed more easily in big data problems. Data visualization tools for R (ggplot2) and Python (Matplotlib, Seaborn) will be covered in the program.
Participants will learn how to:
- Recognize the role of machine learning in the broader spectrum of analytics
- Build machine learning models using the most widely-used tools (R and Python)
- Assess and compare models developed by different algorithms
- Deploy machine learning models to solve practical business problems
- Recommend the best machine learning algorithms for detecting trends in large, noisy data sets
- Compare and contrast data mining and machine learning techniques based on their mathematical assumptions, scalability, limitations, and parameters
Who should attend
This program is for professionals seeking to optimize business performance in high-tech companies. Applications include business intelligence, data mining/warehousing, service delivery, product development, marketing, and process improvement.