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Artificial Intelligence & 
Machine Learning

What is
Artificial intelligence (AI) covers anything which enables computers to behave like humans, by learning from data and examples, without being explicitly programmed.    
Machine Learning (ML) is a subset of artificial intelligence that is concerned with the “extraction of patterns” from data sets. This means the machine can find rules for optimal behavior but also can adapt to changes in the world.  


Artificial neural networks are a subset of machine learning -- they are algorithms based on mathematical models that mimic how neurons in the human brain work. 


Deep Learning (DL) is yet another subset of AI. In fact, it is a subset of machine learning and neural networks. Algorithms are run on “deep neural networks” -- like neural networks but usually with at least three or more incremental layers (complex neural networks).   


In a sense, Artificial Intelligence consists of groups of related techniques comparable to a group of “decision trees.” 

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AI helps solve problems much like humans (more powerfully in numerous instances!)  


The learning algorithms can adjust and make decisions based on processing high volumes of data


Organizations will face the need to adopt AI-related technologies and processes in order to stay competitive, as AI rapidly spans a wider set of industries and use cases. 


Benefit 1

Gain faster insights from data and help your organization make better informed and faster decisions 

We are here to help. 

Nth Generation offers teams of tenured experts that provide the expertise and certifications needed to assist with your AI and machine learning needs.   

Partner with Nth to determine:

AI for IT Ops

Monitors 24/7, predicts problems, proactively resolves problems  


Network, endpoint, file, user, e-mail, and other applications’ behavior analytics, detection and response


Privacy and regulations compliance 

HPE AI Transformation Workshop

  • Evolve your Big Data Analytics initiatives and choose the best use cases for artificial intelligence.  

  • A successful workshop with the right decision-makers and strong client investment intent can achieve:  

  • A common understanding and vision that unifies internal data, business, IT, ITO teams around scope, and initiative  

  • Identification of relevant use case(s) and related priorities  

  • Review of key trends, technologies and terminology for data, AI, analytics, and blockchain to apply holistic framework  

  • Quick discovery of dependencies on, and readiness of, internal and external data sources  

  • A high-level roadmap of projects, priorities for your intelligent data strategy, based on vision and gaps 

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