Cloudera Data Science Workbench Services

Are you looking to tap into the power of Cloudera Data Science Workbench which is a self-service and secure data science platform? Do you want professional data scientists to use Cloudera Data Science Workbench to manage your analytics pipelines so that you can accelerate your machine learning projects right from exploration and design through to production? Are you looking for professional and specialized help to use Cloudera Data Science Workbench to run experiments with your preferred data science packages together with access to computing resources as and when you need them? Are you looking to centrally train, deploy, and manage your models for enhanced compliance, performance, and agility? If so, you can benefit significantly from our Cloudera Data Science Workbench services.

Flatworld Solutions (FWS) is a leading Cloudera Data Science Workbench company and can provide you with experienced and trained data scientists who can use advanced tools like Python, R, and Scala to securely run data computations on Hadoop clusters. Our expert data scientists will help you implement Cloudera Data Science Workbench for your enterprise and directly integrate it with the Cloudera platform so that you gain access to an end-to-end machine learning workflow that can run both on-premises and the public cloud. We will also enable you to unlock the full potential of Cloudera Data Science Workbench and enable your teams to collaborate more efficiently on your projects. If you are looking to deploy a machine learning project right from research to deployment, we can help. Our data scientists will create sophisticated computer algorithms to extract useful information from your data by using Cloudera Data Science Workbench.

Our Cloudera Data Science Workbench Services

We are a leading Cloudera Data Science Workbench service provider and can help throughout your machine learning project, right from research and design through to deployment.

Our Cloudera Data Science Workbench services include -

• Exploring and experimenting with different data sets
• Deploying automated analytics pipelines
• Training and evaluating models
• Deploying models as REST APIs
• Using Python, R, or Scala to run data computations
• Sharing research with your team
• Ensuring quicker time to production without the need for recoding
• Scheduling, tracking, and email alerts
• Accessing Hadoop data and running Spark queries
• Building, training, and deploying machine learning models
• Creating interactive web dashboards and apps