Machine Learning | News, how-tos, features, reviews, and videos
Data analytics and machine learning can deliver real business value, but too many projects miss their mark. Here are seven mistakes to watch out for, and what to do instead.
Submission Deadline: Friday August 30, 2024 5:00PM ET
Fueled by vibes and with stars in their eyes, enterprises are not taking the time to understand generative AI’s limitations and to create their own rules-based approach.
To create effective machine learning and deep learning models, you need copious amounts of data, a way to clean the data, and a way to train them, deploy them, and keep them updated. The cloud is usually the best platform for this, but not always.
A brief guide to data visualization, data analytics, and data science platform capabilities and differences, and seven steps to selecting the right data platform for your needs.
Fabric updates announced at Build 2024 also include Snowflake and Databricks integrations and the general availability of Copilot for Power BI.
Developing generative AI applications is very different from developing traditional machine learning applications. These are the steps.
Other updates include grounding applications and virtual agents in Google Search via Vertex AI and Vertex AI agent builder.
Hardware requirements vary for machine learning and other compute-intensive workloads. Get to know these GPU specs and Nvidia GPU models.
Companies investing in generative AI find that testing and quality assurance are two of the most critical areas for improvement. Here are four strategies for testing LLMs embedded in generative AI apps.