Charles Martin, PhD, data scientist, machine learning AI consultant, and chief scientist at Calculation Consulting, delivers a thorough overview of the technologies that are helping companies expand their customer base and increase revenue. Martin is an experienced professional in machine learning, deep learning, data science, and AI software development. He has a long history in the technology field and was instrumental in the development of machine learning systems for major corporations and companies such as GoDaddy, Aardvark (acquired by Google), eBay, and Blackrock. Martin assisted Demand Media in their successful mission to become the first $1B IPO since Google. His specialization in software engineering and ML experience has made him a top consultant for many companies. Additionally, Martin is a full stack developer for web, object oriented, and numerical programming. Martin earned his PhD in Theoretical Chemistry from the University of Chicago. Martin gives an overview of his company and explains how they specialize in AI and machine learning with a keen focus on translating research into products. Calculation Consulting operates primarily in three areas, strategy, data science, and product development. In regard to strategy, the company seeks to find ways to design new products and predict revenue streams from aggregate data. Regarding data science, their team provides data solutions by applying machine learning algorithms to discover the essential patterns that can drive traffic, engagement, and sales. And in product development, Calculation Consulting builds and deploys contemporary, end-to-end, highly sophisticated, cloud-based software systems. The technology visionary discusses some of the areas his company excels in, such as semantic search and matching. Semantic relates to ‘meaning’ in language. Semantic search improves search accuracy by more fully understanding a searcher’s intent via the contextual meaning. By utilizing concept matching, synonyms, and natural language algorithms, a semantic search can produce a better interactive search and deliver more specific personalized results. He discusses some of the prototypes he has built in this area of the tech field. Martin expounds upon the ways that research has progressed especially thanks to Kaggle, the successful online community of data scientists and machine learners that is powered and owned by Google, Inc. Kaggle enables its many users to locate and publish data sets, to intensely explore and build models in a web-oriented data-science environment, work in connection with other data scientists, enter their work in competitions, and so forth. Martin explains how Facebook, Google, and Amazon alone have put thousands of their top engineers to work on these types of open source projects to develop the most innovative research and turn it into real tools and products. He discusses some of the top open source tools for natural language processing, and his techniques for running them in actual production, working with queries, etc. in the real world. He explains that the process of pulling all this information together, understanding how to utilize the techniques, methods, etc. is an area of their particular expertise. Martin explains in detail the methods of analyzation and how the technology is useful in a practical business work environment. He discusses their project phases and how they assist companies, citing specific examples of companies they have helped, to use neural networks to solve business-specific problems. Martin discusses click-thru and view prediction models, and gives examples of businesses that Calculation Consulting has assisted in their quest to learn more about customer behavior to increase revenue. Specifically, Martin details ways to increase click-thru efficiency using machine learning, and other tips to drive interest and sales. The machine learning specialist relates how, today, there are so many problems that can be solved vi