色导航 in the News, Q4 2022
Ready to Begin Your AI Journey? 3 Steps Financial Advisors Can Take Now
Wealth management is benefitting from recent advances in AI. Alerts can now be generated for when financial status鈥 change. In this , shares how deep learning is ideal for complex data analysis. Jen state鈥檚 that 鈥淩obo-advisors are good examples of deep learning at work. They analyze a customer鈥檚 risk tolerance and current financial trends to make investment recommendations.鈥
5 Things Your AI/ML Training Data Is Lacking
shares his insights on ensuring the data that AI technology companies deploy contains inclusive data and runs efficiently. He identified and how to improve in these areas.
Why Data Remains the Greatest Challenge for Machine Learning Projects
Quality data is both a catalyst to successful AI deployment and the biggest challenge companies will face. looked to our for the insights behind why and how to overcome these challenges. also shared advice and observations for ensuring appropriate steps are taken in obtaining high quality data.
Why the Biggest Obstacle to Machine Learning Initiatives is Data
looked at our for insights into why successful AI is dependent on quality data. The identified areas of focus include organisational structure, corporate policy and leveraging and evaluation.
Pre-Labeled Datasets Are Key to Building High-Quality ML Models
shares her thoughts on the By leveraging PLDs, data is free from personally identifiable information (PII) and ready to be used to train a machine learning module. Jen also shares our solution to making sure our are free from PII and ready to be used for various projects.
Big Data Industry Predictions for 2023
has shared their predictions for what鈥檚 in store for AI, technology, and data in 2023. shares her predictions on speed and quality of data and why companies that normally consider these two elements separately should be focusing on both in tandem to achieve success in the new year.