Machine Learning Software Review Training 
O'Reilly Media - Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. We’ll review methods for debugging below. How is debugging conducted today?
AWS Machine Learning - AI
NOVEMBER 6, 2024
These powerful models, trained on vast amounts of data, can generate human-like text, answer questions, and even engage in creative writing tasks. However, training and deploying such models from scratch is a complex and resource-intensive process, often requiring specialized expertise and significant computational resources.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
O'Reilly Media - Data
JUNE 5, 2018
Why model development does not equal software development. Today, just 15% of enterprises are using machine learning, but double that number already have it on their roadmaps for the upcoming year. So what should an organization keep in mind before implementing a machine learning solution?
Xebia
FEBRUARY 28, 2025
The time when Hardvard Business Review posted the Data Scientist to be the “Sexiest Job of the 21st Century” is more than a decade ago [1]. Both the tech and the skills are there: Machine Learning technology is by now easy to use and widely available. Why is that? … that does not make things easier.
CIO
OCTOBER 29, 2024
This will require the adoption of new processes and products, many of which will be dependent on well-trained artificial intelligence-based technologies. Stolen datasets can now be used to train competitor AI models. AI companies and machine learning models can help detect data patterns and protect data sets.
AWS Machine Learning - AI
NOVEMBER 27, 2024
Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length. This approach reduces memory pressure and enables efficient training of large models.
CIO
DECEMBER 3, 2024
CIOs and other executives identified familiar IT roles that will need to evolve to stay relevant, including traditional software development, network and database management, and application testing. And while AI is already developing code, it serves mostly as a productivity enhancer today, Hafez says. But that will change. “As
Expert insights. Personalized for you.
282 
Let's personalize your content