The Most Admired Global Indian 2021 Award
Aruna Pattam is a Global AI thought leader who has exceptional expertise and wisdom. A remarkable personality who always inspires young souls to chase their dreams. We are exuberant to have Aruna Pattam, one of the great leaders with us on our...
“AI Changemaker Leader 2022” – part of 3AI’s ACME Awards 2022.
3AI congratulates Aruna Pattam, Head AI & Data Science- Asia Pacific & Middle East Region, HCL Technologies being recognized as the winner of #3AIAcme Awards 2022 in AI Changemaker Leader Awards category https://lnkd.in/ghustiF3 AI Changemaker Leader Awards aims to recognize the contributions of industry and...
What is Machine Learning Life Cycle?
When we have a project idea or a dataset and want to predict an outcome such as loan default or customer churn, then we need to build a machine learning model and this involves a series of steps called machine...
How to align AI & BI Business Outcomes
Are you intrigued to learn more about how to align AI & BI Business Outcomes? Listen to this webinar.
MLOps – For building a trusted AI system
How can we scale the technology and build trusted AI with a sense of fairness for all aspects of data science? Learn how MLOps helps to address the challenges of ML and build a trustable AI system.
Unlocking the potential of your enterprise data with AI
Enterprise data forms a key part of the modern-day digital transformation strategy. However, when it comes to leveraging the value that data represents for businesses today, what happens after your data strategy has been set into action makes all the difference. This...
How Artificial Intelligence is transforming the banking sector
Artificial Intelligence (AI) is one technology that’s going to change the way banking will operate. Consumers are increasingly turning to digital-only banks, and even the traditional banks have started to offer more online services.
Key Challenges with Machine Learning Models
While more and more machine learning models are being experimented, there are still few challenges that needs to be still addressed: Bias: Data Bias might exist in the historical credit decision data that is used for training the model drawn...