Artificial Inteligence Data DevOps Machine Learning 
CIO
JUNE 11, 2024
The company is offering eight free courses , leading up to this certification, including Fundamentals of Machine Learning and Artificial Intelligence, Exploring Artificial Intelligence Use Cases and Application, and Essentials of Prompt Engineering. AWS has been adding new certifications to its offering.
TechCrunch
APRIL 7, 2021
As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. Data scientists can download the open-source project and build a machine learning application, but it requires a certain level of technical aptitude to make all the parts work.
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DevOps.com
APRIL 21, 2023
With the rapid advancement of artificial intelligence (AI) and machine learning (ML), companies need to understand and evaluate their readiness to adopt these technologies and drive material business outcomes.
Dzone - DevOps
JANUARY 5, 2024
Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized the way we approach problem-solving and data analysis. However, deploying and managing ML models in production environments can be a daunting task.
Advertiser: Data Robot
Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Collecting and accessing data from outside sources.
AWS Machine Learning - AI
DECEMBER 5, 2023
New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or break a business’s competitive advantage.
Altexsoft
JULY 23, 2020
When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. MLOps vs DevOps.
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