Data Science Workflow Automation
Insights refers to a uniform understanding of a particular business behavior you are able to achieve by using machine learning and artificial intelligence (AI) technology to analyze a dataset.
Our dashboarding allows average users of all skill types to understand what the data models are doing “behind the scenes,” which is especially important when it comes to highly regulated industries like banking and healthcare.
The Marketplace includes automated machine learning, making it easier to build and use machine learning models & techniques in the real world by running systematic processes on raw data and selecting models that pull the most essential information from the data – what is often referred to as “the signal in the noise.”
These marketplace application connectors incorporates machine learning best practices, data sources, & computation styles from top-ranked data science teams to make artificial intelligence pipelines more accessible across the any organization.
There are no fixed frameworks or designated defined templates for solving a new data science dilemma. When confronted with the challenges involved in it you must design the solution to the problem.
This strategy changes with every new dataset of for various projects. But techniques we applied to solve the problem are almost similar to many different problem workflows. We aggregated the high-level data science workflows for all types of problems which are used widely across the market to dvelop this tool.
Choose the perfect plan
If you have a small data project to complete or a multi-faceted data expansion. We allow you to right size your plan to your team. Let use automate your data across your organization.
Frequently asked questions
Automated machine learning is the process of automating the process of applying machine learning to real-world problems. AutoML covers the complete pipeline from the raw dataset to the deployable machine learning model. AutoML was proposed as an artificial intelligence-based solution to the ever-growing challenge of applying machine learning. The high degree of automation in AutoML allows non-experts to make use of machine learning models and techniques without requiring becoming an expert in the field first.
We automate the design, configuration, and implementation of an CRISP-DM data science pipeline.
CRISP-DM: Defined to standardize a data mining process across industries, CRoss-Industry Standard Process for Data Mining (CRISP-DM) is the most well-known framework used to define a data science workflow. Each phase (Business understanding, data understanding, data preparation, modeling, evaluation and deployment) has its own defined tasks and set of deliverables such as documentation and reports. Projects can “loop back” as needed to a previous phase.
Our data science automation workflow platform will reinforce an experience or engagement & transparency. Including team communication, project management, workflow creation, algorithm codebook, and team member task assignment.
We prefer to customize our service for each perspective client. Feel free to schedule an appointment with us so we can better understand how you currently operate and determine your future needs.
Yes, we are always excited to bring more talent to our team.
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If you don’t see a position for you but you think your skillset would be a good fit feel free to send us an e-mail.