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Data Mining and Preprocessing Services

Our ML experts assist you in data labeling, data annotation & data transformation, at scale

As Machine Learning (ML) undergoes constant evolution, the steps involved in ML projects are constantly changing. However, one of the most crucial stages in a machine learning project has been that of data mining and preprocessing. It is important for humans to identify and annotate data accurately so that the machine learning model can learn to classify information and hone its prediction capabilities. Embitel specializes in data mining and preprocessing activities related to various industries.
Automotive

Automotive

Industry 4.0

Industry 4.0

Healthcare

Healthcare

Sports

Sports

Best Practices in Data Mining and Preprocessing

We provide high quality data mining & preprocessing services pertaining to audio, video, text & image data. Our AI/ML experts are also highly qualified to handle data for complex ML models.

Data Security

Data Security

Subject Matter Expertise

Subject Matter Expertise

Quick and Efficient

Quick and Efficient

Personalized Solution

Personalized Solution

100% Transparency

100% Transparency

Native and Cross-Platform

Cross-Platform Integration

Automate and Simplify your business processes with our Machine Learning Solutions. We assure you breakthrough results!

Frequently Asked Questions on Data Mining

Do you provide assistance in Data Annotation?

Yes, we assist customers in converting raw data to “smart” data to train the machine learning model, through data annotation.

 

Data annotation and labeling are both part of data preprocessing. Data cleaning and labeling fall under the annotation process.

Data curation is a type of cleaning process for the data. If there are some unexpected spikes in data, this information is removed before the data is fed to the ML algorithm. For instance, temperature data may come within a standard range. But one or two values may be zero or a very high value. This may be due to sensor errors, a sudden unexpected spike in temperature, etc. This data is removed before it is provided as training data to the algorithm.

What type of Data Transformation services do you provide?
Structural tagging and data enrichment specific to the domain is done as part of our data transformation activities.

Vital pieces of information are added to the raw data and it is structured in such a way that the ML algorithm can process it. Data is also linked or cross-referenced, as needed by the algorithm.

Data may be recorded in an environment with some specific settings, but for the algorithm, we may need it in different settings. So, we need to transform that data to a suitable format. An example is the conversion of data from Fahrenheit to Celsius to suit the algorithm. Another example is the data collected by a sensor that was mounted horizontally. If the algorithm expects data from the sensor in vertical alignment, we transform the collected data to suit the algorithm.
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