Building data science products? Think business first!

Modern machine learning libraries are both a blessing and a curse. Due to the ease with which the libraries can be used, most users (newbies and practitioners alike) focus too much on tools and techniques. We will discuss the high-level thinking process of coming up with a machine learning algorithm by asking a business question before even thinking about the tools or technologies.

Outline: 
• Why starting with technology is the wrong approach? Ask a business question and work your way backward
• Choosing the right machine learning algorithm for your business problem
• High-level thinking process in conceiving, implementing, deploying and maintaining a machine learning system

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Raja Iqbal
About The Author
- Raja Iqbal is a data scientist, a passionate educator, and an internationally recognized speaker on all things data science. He is the Founder and Chief Data Scientist at Data Science Dojo. Prior to Data Science Dojo, Raja worked at Microsoft in a variety of research and development roles involving machine learning and data mining at very large scale. Raja has a Ph.D in Computer Science from Tulane University with a focus on machine learning and data mining.

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