The AI Leader’s Cheatsheet: Enhancing Accuracy & Reliability of AI Models
As a Data Leader or CTO of an AI company, staying at the forefront of AI model development is crucial for success. This cheatsheet provides a comprehensive guide to enhance the accuracy and reliability of AI models. From dataset preparation and handling biases to training and evaluating models, this resource empowers AI leaders to drive their teams towards building cutting-edge and ethical AI solutions.
Building a Robust Dataset for Effective AI Model Training
AI model benefits from a dataset that is consistent, rich in features, free from biases, and of sufficient size. To construct a robust data pipeline for AI model training, organizations should prioritize consistency, richness of features, handling missing data, addressing biases, and ensuring sufficient dataset size.
Step 1: Striving for Consistency
Consistency is crucial in labeling and formatting each case within the dataset. In the case of VideoHealth, a dental…
