Cognegica Networks, provides superior quality human annotated data at large scale from Globally Distributed Skilled Workforce of Experienced Annotators for supervised machine learning models and for its applications.

What is Machine Learning?

Machine Learning (ML) is an application of Artificial Intelligence (AI) where a machine learns and improves itself; through data analysis and algorithms.

Machine learning is specifically of two types – Supervised Learning and Unsupervised Learning.

In Supervised Learning, training data gets fed to the machine with labelling on specific points and patterns. It trains the system to identify these patterns in real-world scenarios.

In Unsupervised Learning, the machine is inputted with unlabeled data and has to infer the patterns and outliers on its own through intense analysis.

Cognegica Networks provides machine learning training to AI models in the cybersecurity space.

Machine Learning Training for Cybersecurity

There are numerous applications of ML to combat cybersecurity threats. Detection of fraudulent online transactions to spam detection, ML algorithm is nothing short of a messiah in this tech-savvy world.

ML algorithms efficaciously analyze a vast amount of historical data to identify patterns and ‘normal’ behavior. Such kind of supervised learning is almost impossible for human resources to undertake with excellent accuracy. 

One of the vital benefits of using AI and ML in the cybersecurity space is in thwarting the spread of an attack from one host to multiple hosts. Machine learning algorithms are capable enough to understand there is an attack on a host machine; it immediately takes necessary steps to contain the attack only to that host.

All of these crucial applications of machine learning in cybersecurity need a relevant and well-compiled training data set. The training data sets are the foundation of your ML engine in an AI set-up, as the machine uniquely trains to perform its tasks based on this data set.

Cognegica Networks undertakes ML training services for various clients for their AI projects. We gather a thorough understanding of a client’s wants and their models before providing them custom training data sets as per their requirements. Different models need different training; also, the algorithm developed by every company is unique to them. Our team uses the threshold values, truth tables, etc., to train the ML models.

Training Procedure

Following are the steps we follow to train the ML engine.

1. Identify the set of tasks that the machine will perform.
2. Gather and prepare the data to be inputted.
3. Divide the data into a training set and test set.
4. Input the data and run the algorithm; the ML model trains on this data. The hyperparameters fine-tune at this stage.
5. After training, evaluate the model on a test data set.
6. If it performs as per expectations, then the machine is set for use. If not, repeat the above steps till we are sure of the algorithm’s performance.

A dedicated team at Cognegica Networks specializes in machine learning training for artificial intelligence models and engines. If you would like us to partner with you for the same, then you can contact us here for this service.