Pixelette Technologies

Services of Unsupervised Learning

Unsupervised learning is a subset of a machine learning program that is used to draw inferences from datasets consisting of stored data without classifying responses. The most common unsupervised machine learning method is cluster analysis that we use for exploratory data analysis to find hidden insights or grouping in data.
Importance of unsupervised learning:
Here are prime reasons for using this type of machine learning technique:

  • Unsupervised machine learning finds all kinds of unknown patterns in data.
  • Unsupervised methods help you to find features that can be useful for categorization.
  • It has taken place in real-time. So all the input data is analyzed and labeled in the presence of learners.
  • It is easier to get unlabeled data from a computer than labeled data, which needs manual intervention.

Types of unsupervised learning

Unsupervised machine learning can be further divided into the following categories:

  • Clustering

This concept is extremely important when you need to handle uncategorized data. The clustering algorithms scan the data to process and find the natural groups existing. The limit on how many clusters or groups that you need to identify in the uncategorized data can also be set.

  • Association

This type of model helps you determine if the elements in the data are associated with each other or not. For instance, determining the products that users are buying in pairs.

  • Outlier Detection

Such models are used to scan the data to identify any sort of dissimilarity and abnormalities in the dataset. Its most important application is identifying any fraud in credit card transactions.

  • Auto-encoders

This type of model includes the compressing of input into coded form. The most well-known real-life example of such a model is improving the quality of image and video.

Our services:

We will help you to automate your complicated computer systems with unsupervised machine learning. Our AI engineers build a proficient unsupervised algorithm to work smoothly on an extensive and complex dataset. We use intelligent machine learning models, such as Clustering, Association Mining, Latent Variable Model, and Anomaly Detection for automatically identifying the group of unlabeled training data. Once you find the hidden structure of the dataset, you can increase the efficacy, productivity, and overall performance of the system. It helps us in building automated and highly engineered products for an optimal outcome.


Our services will be beneficial for your business.

  • Business profitability

We provide a wide range of business benefits through an unsupervised machine learning approach. You can use it on industries’ significant departments, such as human resources, finance, customer support, marketing, and sales.

  • Interpret past behavior

Our innovative unsupervised methods quickly infer the complicated systems for accurate prediction.

  • Budget-friendly

Evaluate the efficiency of your systems with our competitively priced services.

  • Rapid analysis

The machine learning technology takes minimum time to analyze unlabeled data.

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