Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.
In this virtual bootcamp, we’ll cover best practices and hands-on labs that will help demonstrate how you can use Databricks Unified Data Analytics platform to simplify and scale your data and ML efforts.
We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources. You’ll learn how to use ML frameworks (i.e. TensorFlow, XGBoost, Scikit-Learn, etc.) to train models based on different requirements.
And finally, you can learn how to use MLflow to track experiment runs between multiple users within a reproducible environment, and manage the deployment of models to production.
Secure a seat and learn how Databricks is able to support your business by bringing data science, business analytics, and engineering together to accelerate your data and ML efforts.
- Learn how to build highly scalable and reliable pipelines for analytics.
Interact with Spark and Databricks experts in our live Q&A.
- Get practical advice and tips on how to get your data analytics & ML projects started with our live hands-on labs.
Discover insights to answer questions around Big data: What can it do for my industry? How can I explain its value to my colleagues and company leadership?