Data science, big data and predictive analytics are often misunderstood. The goal of this talk is to provide an overview of a typical big data pipeline, and provide a gentle introduction to the discipline of data science and predictive analytics. We will discuss at high level how some of the common machine learning algorithms are used by major big data companies to gain actionable insights, improve customer experience and gain competitive advantage in their respective industries.
• Provide an end to end overview of a big data pipeline.
• Understand how queries, page views, clicks and other forms of user interaction are used in a big data pipeline to gather actionable insights.
• View some examples of how Amazon, Google, FB and other big data companies may be using data science
• Discuss some examples from online search, advertising, retail, insurance, social networks, entertainment, education, healthcare, telecommunication and law enforcement.
• Provide a high level overview of some of the common data mining tasks like regression, classification, clustering, association analysis and outlier detection. This will be a very high level overview of these techniques without getting into the technical details.
• Understand descriptive, predictive and prescriptive analytics methods and when, where and how they are useful
• Discuss the various challenges in big data related tasks
Who Should Attend:
Anybody with an interest in understanding the bigger picture of big data and data science.
About The Presentator:
Raja has worked in various research and development roles at Microsoft Online Services Division. During his tenure, he worked on various cutting edge techniques that deal with various problems in paid search marketplace, online advertising, relevance in online retrieval, data mining at large scale, predictive analytics and online experimentation.
At Microsoft, Raja has been a regular speaker at various tech-talks and tutorials. He delivered a lecture series titled ‘Introduction to Machine Learning’ that has been a recommended resource for new Microsoft OSD employees for many years. He has also given talks on predictive modeling, R programming, online experimentation and A/B testing, relevance in online systems and online advertising. Raja has published his work on object detection, DNA classification, face detection and texture classification in peer reviewed journals and conferences. He has also served as reviewer for various journals and conferences in machine learning, data mining, artificial intelligence and large scale online systems. In 2013, Raja quit Microsoft after catching the entrepreneurship bug. He is currently working on his startup.
Most recently, Raja has been working on creating a high quality predictive analytics training program that includes classroom training and a mentor guided participation in a Kaggle competition. Details of this workshop can be found here: http://datasciencedojo.com/workshops/hands-on-predictive-analytics/