Introduction In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. This year, we expanded our partnership with NVIDIA, enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using […]
Introduction In our previous blog post in this series, we explored the benefits of using GPUs for data science workflows, and demonstrated how to set up sessions in Cloudera Machine Learning (CML) to access NVIDIA GPUs for accelerating Machine Learning Projects. While the time-saving potential of using GPUs for complex and large tasks is massive, […]
When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks. To overcome this, practitioners often […]
This is part 4 in this blog series. You can read part 1 here and part 2 here, and watch part 3 here. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing […]
Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. The implications of ML on the future of business are clear. However, only 4% […]
The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. It builds on a foundation of technologies from CDH (Cloudera Data Hub) and HDP (Hortonworks Data Platform) technologies and delivers a holistic, integrated data platform from Edge to AI, helping clients to accelerate complex […]
Introduction Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. For data professionals that want to make use […]
In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. You will learn all the parts of Cloudera’s Data Platform that together will accelerate your everyday Data Worker tasks. This […]
2020 is a year that’s been defined by transformation. The way we work, how businesses operate, and even serve customers have all transformed in order to cope with the challenges that have been thrown our way. Amongst the chaos, some organizations have excelled. The Industry Transformation category at our Data Impact Awards celebrates these organizations— […]
In our last two posts, we talked with Deloitte’s Marc Beierschoder and Martin Mannion respectively about the requirement organizations have to deploy their data and analytics, quickly, into a hybrid environment. On top of that, there is the fundamental aspect of consistent security and governance of your enterprise data cloud and need for multiple users […]
