Machine learning is a type of artificial intelligence that provides machines the ability to automatically learn from historical data to identify patterns and make predictions. Machine learning implementation can be complex and success hinges on using the right integration, management, and analytics foundation.

The Avalanche Cloud Data Platform is an excellent choice for deploying machine learning, enabling collaboration across the full data lifecycle with immediate access to data pipelines, scalable compute resources, and preferred tools. In addition, the Avalanche Cloud Data Platform streamlines the process of getting analytic workloads into production and intelligently managing machine learning use cases from the edge to the cloud.

With built-in data integration and data preparation for streaming, edge, and enterprise data sources, aggregation of model data has never been easier. Combined with direct support for model training, systems, and tools and the ability to execute models directly within the data platform alongside the data can capitalize on dynamic cloud scaling of analytics computing and storage resources.

The Avalanche Platform and Machine Learning

Let’s take a closer look at some of the Avalanche platform’s most impactful capabilities for making machine learning simpler, faster, accurate, and accessible:

1. Breaking down silos: The Avalanche platform supports batch integration and real-time streaming data. Capturing and understanding real-time data streams is necessary for many of today’s machine learning use cases such as fraud detection, high-frequency trading, e-commerce, delivering personalized customer experiences, and more. Over 200 connectors and templates make it easy to source data at scale. You can load structured and semi-structured data, including event-based messages and streaming data without coding
2. Blazing fast database: Modeling big datasets can be time-consuming. The Avalanche platform supports rapid machine learning model training and retraining on fresh data. Its columnar database with vectorized data processing is combined with optimizations such as multi-core parallelism, making it one of the world’s fastest analytics platforms. The Avalanche platform is up to 9 x faster than alternatives, according to the Enterprise Strategy Group.
3. Granular data: One of the main keys to machine learning success is model accuracy. Large amounts of detailed data help machine learning produce more accurate results. The Avalanche platform scales to several hundred terabytes of data to analyze large data sets instead of just using data samples or subsets of data like some solutions.
4. High-speed execution: User Defined Functions (UDFs) support scoring data on your database at break-neck speed. Having the model and data in the same place reduces the time and effort that data movement would require. And with all operations running on the Avalanche platform’s database, machine learning models will run extremely fast.
5. Flexible tool support: Multiple machine learning tools and libraries are supported so that data scientists can choose the best tool(s) for their machine learning challenges, including DataFlow, KNIME, DataRobot, Jupyter, H2O.ai, TensorFlow, and others.

Don’t Take Our Word for It

Try our Avalanche Cloud Data Platform Free Trial to see for yourself how it can help you simplify machine learning deployment. You can also read more about the Avalanche platform.

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