Pickl AI
APRIL 27, 2023
Data Analytics Trend Report 2023: Data Science is an interdisciplinary field that focuses on filtering the data, categorizing it, and deriving valuable insights. As the importance of Data Science and its role continues to grow, so does the demand for data professionals. billion by 2030.
Unite.AI
OCTOBER 12, 2023
In June 2023 you were recruited as Vice President of Technology at LXT , what attracted you to this position? Throughout my academic and professional experience prior to LXT, I have always worked directly with data. What is your vision for how LXT can accelerate AI efforts for different clients?
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Unite.AI
MARCH 14, 2024
Finally, AI strategy and training data constitute the largest allocations within AI budgets, signifying the strategic emphasis on laying a robust foundation for AI initiatives through comprehensive planning and quality data resources.
Snorkel AI
AUGUST 24, 2023
Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.
Snorkel AI
AUGUST 24, 2023
Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.
Snorkel AI
AUGUST 24, 2023
Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.
John Snow Labs
OCTOBER 19, 2023
One reason for this bias is the data used to train these models, which often reflects historical gender inequalities present in the text corpus. To address gender bias in AI, it’s crucial to improve the data quality by including diverse perspectives and avoiding the perpetuation of stereotypes. abs/2304.07683 Ma, M.
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