Let’s welcome the top data science influencers of the past month. Here we discuss personalities and who have done brilliant work in the field of data science, analytics, artificial intelligence & machine learning in the past months.
Bernard Marr is a bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI, AI & Big Data guru. Not only is he the advisor of many of the world’s best-known organizations but also is the author of 18 best-selling books. He also writes a regular column for Forbes. He has 2 million social media followers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.
Bernard Marr was recently interviewed where he talked about how Artificial intelligence gives companies superpowers. Artificial intelligence is already becoming a big part of our daily lives. It is helping to personalize our internet searches, filtering spam, helping banks detect fraud. Any company that is not seriously thinking about applying artificial intelligence will simply be left behind. For a strategic use of artificial intelligence, companies need to develop AI competencies internally and create a culture of innovation. Business leaders must keep up with developments in AI. In that way, they can reorient and reimagine their businesses to thrive during the intelligence revolution.
Josh Bersin is the president and founder of Bersin & Associates, leading industry research and advisory firm in enterprise learning and talent management. Bersin is the author of The Blended Learning Book from Pfeiffer, and The High-Impact Learning Organization and High Impact Talent Management. He is an industry analyst, researcher, educator, and technology analyst. He covers all aspects of corporate HR, training, talent management, recruiting, leadership, and workplace technology.
Last month, Josh wrote an article about why elevating equity is the challenge of the decade for HR. This attracted enthusiasts in fields that deal with the challenges and trends impacting business workforces around the world. One of the core concepts of workforce management includes the involvement of HR and WFM analytics. One of his most startling findings has been that DEI training is one of the least impactful practices. There were millions of dollars invested on that over the last years. They also found that only one company in five holds itself accountable for equity and inclusion in its business practices. However, roughly 40% of companies still see DEI as an issue of risk mitigation and compliance, not a strategic imperative.
Latanya Arvette Sweeney is a Professor of the Practice of Government and Technology at Harvard University. She is also the Director of the Data Privacy Lab in the Institute of Quantitative Social Science at Harvard. In addition to that, she is the Faculty Dean in Currier House at Harvard. Professor Sweeney creates and uses technology to assess and solve societal, political, and governance problems. In addition to that, she teaches others how to do the same. Data Privacy is one of the focus areas. She also holds the privacy and security seat of the Federal Health Information Technology Policy Committee. She is one of the leading data science influencers of the workd through her work for data protection and privacy.
Her name was recently mentioned in an article that spoke about how public-interest technologists can build a government that works for everyone. She was cited as the best example of someone who does not require industry experience in order to bring public interest technology experience. Latanya Sweeney is a pioneer of the algorithmic fairness field. She founded the Data Privacy Lab at Carnegie Mellon and moved that work to Harvard. She then became the chief technology officer at the Federal Trade Commission.
Thomas Hayes“Tom” Davenport, Jr. is an American academic and author specializing in analytics, business process innovation, knowledge management, and artificial intelligence. Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College. He is also the co-founder of the International Institute for Analytics. In addition to that, he is a Fellow of the MIT Initiative for the Digital Economy, and a Senior Advisor to Deloitte Analytics. He has twenty books and over 250 print or digital articles for Harvard Business Review(HBR) to his name, along with the Sloan Management Review, the Financial Times, and many other publications. He earned his Ph.D. from Harvard University. In addition to that, he has taught at the Harvard Business School, the University of Chicago, the Tuck School of Business, Boston University, and the University of Texas at Austin.
He recently wrote an article about‘Enterprise Adoption and Management of Artificial Intelligence’. He mentioned that Artificial intelligence is the most important new technology of the age. However, it comes in many varieties, and businesses face a range of challenges in effectively deploying it throughout their organizations. Tom Davenport takes a practical but positive approach to the long-term potential of AI. In addition to that, he describes it as one of the most effective approaches to creating and implementing a strategy for this transformative technology. He believes that if a company wants to use AI to create a competitive advantage, it must adopt the technology broadly and aggressively. Surveys suggest that many executives feel that AI will have a transformative impact on their businesses and industries.
Gregory I. Piatetsky-Shapiro is a data scientist and the co-founder of the KDD conferences. In addition to that, he is the co-founder and past chair of the Association for Computing Machinery SIGKDD group for Knowledge Discovery, Data Mining, and Data Science. He was no. 1 on LinkedIn Top Voices in 2018 on Data Science and Analytics. His specialties include Data Mining, Business Analytics, Data Science, Predictive Analytics.
He is on of the leading data science influencers, being the president of KDnuggets(since 1997), he is behind all the amazing articles that are published on this blog related to data science, artificial intelligence, and machine learning. The concepts of statistics that one should know before attending data science interviews is one of the best coming from his firm. Through KDnuggets his main focus is to cover the fields of Business Analytics, Data Mining, and Data Science, including interviews with key leaders. Under him, they have also published an article about evaluating Object Detection Models using Mean Average Precision and the skills needed to become a data science engineer. He is also quite vocal about this firm on LinkedIn, where he shares his favorite picks, interesting reads, and insightful knowledge about data science that requires attention. Approaching(Almost) every Machine Learning problem is one of them.
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