Learn exactly what AutoML is, the value data scientists bring, and best practices on how to use AutoML to kickstart projects within your business.
Archives for July 2022
Deployment Risk: AutoML & Machine Learning Without Expertise
Azure empowers easy-to-use, high-performance, and hyperscale model training using DeepSpeed
This blog was written in collaboration with the DeepSpeed team, the Azure ML team, and the Azure HPC team at Microsoft. Large-scale transformer-based deep learning models trained on large amounts of data have shown great results in recent years in several cognitive tasks and are behind new products and features that augment human capabilities. These […]
An Insider’s Look at Intuit’s AI and Data Science Operation
Intuit’s Director of Data Science speaks with InformationWeek about how the company’s data operations have grown and evolved from just a few data scientists trying to sell executives on the value of data projects to becoming an AI-driven platform company.
4 Principles of Developing an Ethical AI Strategy
How prioritizing responsible artificial intelligence will set your company up for success — and instill trust in your customers
Amazon Redshift Serverless Generally Available to Automatically Scale Data Warehouse
Amazon recently announced the general availability of Redshift Serverless, an elastic option to scale data warehouse capacity. The new service allows data analysts, developers and data scientists to run and scale analytics without provisioning and managing data warehouse clusters. By Renato Losio
Quick Study: Cyber Resiliency and Risk
Cyber resilience is far more than a notebook full of disaster recovery plans gathering dust. This collection of recent articles can help you better understand the challenges that face all types of organizations.
What Can We Do to Address the Gender Gap in Tech Leadership?
Many studies that show tech companies with diverse perspectives perform better than those without. Here’s why companies need to be deliberate in hiring women at all levels.
What Can We Do to Address the Gender Gap in Tech Leadership?
Many studies that show tech companies with diverse perspectives perform better than those without. Here’s why companies need to be deliberate in hiring women at all levels.
Shopify’s Practical Guidelines from Running Airflow for ML and Data Workflows at Scale
Shopify engineering shared its experience in the company’s blog post on how to scale and optimize Apache Airflow for running ML and data workflows. They shared practical solutions for the challenges they faced like slow file access, insufficient control over DAG, irregular level of traffic, resource contention among workloads, and more. By Reza Rahimi