Accelerate your machine learning (ML) projects with three new ML Snap Packs

More and more organizations are searching for ways to drive business value with machine learning (ML), a practical form of artificial intelligence (AI). But conventional approaches to developing and deploying ML models are hampering their efforts. Traditional methods are slow, code-intensive, and require specialized skill sets. What’s more, data scientists and data engineers are forced to spend exorbitant time on data integration activities such as collecting and preparing data.

That’s why we created SnapLogic Data Science, a self-service solution that simplifies the entire machine learning lifecycle. Included with SnapLogic Data Science are three brand-new Snap Packs that accelerate your ML projects. 

ML Data Preparation Snap Pack

Data scientists and data engineers have to perform a host of data integration tasks to create flawless training datasets. They have to gather, organize, cleanse, transform, and label data. These tasks are critical to ensuring that truly representative data is collected, but they are also some of the most time-consuming tasks and require many iterations.

The ML Data Preparation Snap Pack offers a visual drag-and-drop alternative to data preparation, freeing up time for the more strategic aspects of the machine learning development process.

The Snaps in the ML Data Preparation Snap Pack enable you to quickly perform several data preparation operations that are specific to machine learning. You can rapidly convert categorical data to numeric data, generate sample datasets using sampling algorithms, clean missing values, and more, all with minimal to zero coding.

Devote more time to building effective ML models and less time to humdrum integration tasks with the ML Data Preparation Snap Pack.

ML Analytics Snap Pack

To create a machine learning model with high prediction accuracy, you have to train it with a lot of high-quality data. But the data must not only be clean, but it also must be relevant to the problem you want your model to solve. That’s where the ML Analytics Snap Pack comes in. This Snap Pack enables you to analyze your data so you can, among other things, select the right training data for your model.

With the ML Analytics Snap Pack, you can profile your data and generate statistical information for your input dataset. Profiling helps you spot errors, understand the data distribution structure, and determine if you even want to use certain data preparation techniques to sample, scale, and cleanse your dataset.

Gain insights from your data fast with the ML Analytics Snap Pack.

ML Core Snap Pack

As with other parts of the machine learning lifecycle, building, training, and evaluating (testing) a model involves a great deal of manual, time-intensive coding. Developers with skills in Python, Scala, and other programming languages – skills which are sometimes difficult to find – are required at this stage. For example, for an algorithm to ingest and decipher training data, a data scientist must hand-code an integration pipeline(s). This stage of the machine learning process is also highly iterative, meaning data scientists end up writing the same scripts over and over again.

The ML Core Snap Pack, like the others contained in SnapLogic Data Science, provides a visual drag-and-drop interface for building, training, and validating machine learning models.

The ML Core Snaps allow you to easily implement several state-of-the-art algorithms based on mature open source libraries (e.g., linear regression, decision tree, Naive Bayes, and other algorithms). But you don’t have to use our pre-packaged algorithms if you don’t want to. You can instead write native Python in Jupyter Notebooks and operationalize it in SnapLogic. Finally, the Snaps in this Snap Pack also let you rapidly train and validate (cross-validate) your model.

Leverage the ML Core Snap Pack to streamline the model training and evaluation phase of the machine learning lifecycle.

Get started with machine learning today

SnapLogic Data Science and the new ML Snap Packs therein can dramatically increase the productivity of data scientists, citizen data scientists, and data engineers. Consequently, organizations that leverage SnapLogic Data Science will see an increase in the speed and success of their ML projects. Get started with SnapLogic Data Science, in tandem with SnapLogic’s underlying Intelligent Integration Platform, and kick-start your machine learning projects today.

  • Start a free trial of SnapLogic Data Science here.
  • Explore several machine learning applications for image recognition, customer churn prediction, natural language processing, and more on our machine learning showcase site. All the models on the ML Showcase were either developed, deployed, or both using SnapLogic Data Science.

Karen He

Karen He is a Senior Product Marketing Manager at SnapLogic.


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