October 30, 2018
The McKinsey Global Institute predicts that the U.S. will be short 250,000 data scientists by 2024.
By 2021, insights-driven business will steal $1.8 trillion a year in revenue from competitors that are not insights-driven, according to Forrester. Don’t let the budding talent shortage and access to relevant data stop your organization from using machine learning to build powerful models that help you perform predictive and eventually, prescriptive analytics. SnapLogic allows you to leverage their machine learning capabilities on your data, without the need for specialized training in data science.
Learn about how our machine learning solution can be leveraged for a variety of uses such as:
- Building a personalized recommendation engine that increases customer engagement and revenue
- Predicting diabetes or cancer in patients
- Creating models that can identify fraudulent financial transactions, etc.
You can expect to learn:
- The key differences between AI and ML algorithms, Deep Learning, Image Recognition, Handwriting Recognition, Natural Language Processing techniques, etc.
- The additional types of insights you can expect to obtain from Machine Learning
- The Machine Learning process
- How SnapLogic’s machine learning solution helps get you started on your machine learning/data scientist project!
Dr. Greg Benson
Chief Scientist at SnapLogic
SVP of Product Management and Product Marketing at SnapLogic