Can machine learning transform business problems to business values and insights?
“If you invent a breakthrough in Artificial Intelligence, so machines can learn, that is worth 10 Microsofts” - Bill Gates
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level artificial intelligence (AI).
More businesses now realize that business intelligence (BI) is not enough as the volume, speed, and complexity of data now defy traditional analytics tools. While business intelligence addresses descriptive and diagnostic analysis, machine learning unlocks new opportunities through predictive and prescriptive analysis.
Data as a Competitive Asset - Data is now a critical asset that offers a competitive advantage to smart organizations that use it correctly for decision making.
Increased Customer Demand - Increased demand by businesses for predictive analytics as businesses seek more powerful analytical techniques to uncover value from the large amount of data stored in the internal and external systems.
Increased Awareness of Data Mining Technologies - More businesses now understand the business value in Data Mining Technologies.
Access to More Data - Most industry pundits now agree that we are collecting and access to more data than ever before. This data explosion is driven by the rise of new data sources such as social media, cell phones, smart sensors, and dramatic gains in the computer industry. The large volumes of data being collected also enables you to build more accurate predictive models.
Faster and Cheaper Processing Power - We now have far more computing power at our disposal than ever before.
Microsoft Azure - Machine Learning & R Packages
Microsoft Azure Machine Learning offers popular algorithms such as linear and logistic regression, k-means for clustering, decision trees, decision forests (random forests, boosted decision trees, and Gemini), neural networks, support vector machines, and Bayes point machines.
R is an open source statistical programming language that is commonly used by the computational statistics and data science community for solving an extensive spectrum of business problems. R packages are supported in Microsoft Azure Machine Learning provides powerful capabilities for data analysis, visualization, and modeling.
Azure Machine Learning Studio
Amazon Machine Learning is also a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML). Once your models are ready, Amazon Machine Learning makes it easy to get predictions for your application using simple APIs.
“Companies that use data and business analytics to guide decision making are more productive and experience higher returns on equity than competitors that don’t”
—Brad Brown et al., McKinsey Global Institute, 2011
