Accelerate Your Machine Learning Journey

Implement MLOps To Accelerate Your Machine Learning Design-To-Production Journey

As more and more organizations adopt Artificial Intelligence (AI) and Machine Learning (ML), they find that along with seizing the significant opportunities created by these technologies, they need to manage what is perhaps their greatest challenge: scalability.

With the constant acceleration of change in data and analytics, organizations need more from their ML models than exciting use cases and cutting-edge innovation; they need the ability to automate and operationalize the production of AI solutions. Unfortunately, organizations increasingly struggle to turn ML capabilities into viable applications due to an inadequate model development layer.

In this whitepaper, we explore a framework that organizations can use to build a model development layer that makes the process of taking AI capabilities from design to delivering business outcomes far more efficient.

Read this whitepaper to understand:

The game-changing business outcomes made possible by ML
Common model development challenges faced by all organizations as they ramp their ML development efforts
How leading organizations use MLOps to overcome those challenges while streamlining and scaling the entire model development lifecycle
How Refract provides an integrated, turn-key MLOps solution that can be deployed on any infrastructure

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5 ways to foster data curiosity in your business

Just as early humans survived on curiosity to discover fire and invent the wheel, today’s organizations built on data need to know their data terrain well to survive and stay on the top. They need to understand what data resources are available to them and what challenges they face from disruptors, who always keep them on their toes.

A tale of two events: Inside Snowflake’s and Databricks' marquee events

The simultaneous timing of the events did raise some eyebrows in the industry, and soon it became evident that a fierce competition was unfolding between the two powerhouses, both vying for a similar target audience and a larger partner ecosystem. While Snowflake’s spectacular show in Las Vegas boasted over 12000 confirmed attendees, there was an equally palpable excitement in the air for the Databricks event happening in San Francisco.

Accelerate your production ML journey with Refract

As we all know, production ML (Machine Learning) is more engineering than machine learning. Building a prototype in machine learning has become very simple nowadays, all thanks to different open-source projects like sci-kit, TensorFlow, Keras, etc. But operationalizing that model to get the insights from the model which can be used in day-to-day business decisions is challenging and needs more engineering knowledge than data science knowledge.