AI Robot

Artificial Intelligence.

Accelerate the development of your AI solutions with high-level services.

 

Artificial Intelligence is the new oil, according to industry experts. Just as oil had a profound impact in the previous industrial revolution, Industry 4.0 augurs in an era of machines and systems capable of perception and computation. The culmination of this revolution is the holy grail of Computer Science – machines with reasoning capabilities. Enterprises with the objective of digital transformation can take measured steps in retooling their organizations by implementing these new AI technologies. NetObjex is here to help you take that next step.

 
   

The Process.

Once data is gathered, the next one may need to massage the data to convert it into a form that is ingestible by AI models. For instance, something as simple as an address may need to the split into its constituent parts of street number, street name, city, state, zip and country. Such cleansing activities occur at this stage.
Once data is gathered, the next one may need to massage the data to convert it into a form that is ingestible by AI models. For instance, something as simple as an address may need to the split into its constituent parts of street number, street name, city, state, zip and country. Such cleansing activities occur at this stage.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
In Machine Learning, one trains a system to look for patterns. That training process often involves one exposing the models selected from the previous step to typical training data that the system would most likely encounter in everyday use. The better the training data, the better the outcomes that can be predicted through Machine Learning when it comes to real-world scenarios.
Evaluation or Testing involves running various typical data sets against the machine learning models to observe the outcomes predicted. If the outcomes are not accurate, then one may need to feed better training data or tweak the models. This is an iterative process to ensure that in real-life scenarios the predictions made by the AI system are accurate.
Hyperparameters can be thought of as settings that govern the training process itself. So, for instance, in a deep neural network (one of your Machine Learning tools) is a hyperparameter that indicates the number of hidden layers of nodes to use. The process by which these parameters can be adjusted over time by measuring the accuracy of predictions is called hyperparameter tuning.
The ultimate objective of Machine Learning systems is to make predictions. These predictions should not be thought of as end-point but rather as a step in a continuous process. By this, we mean that the predictions serve as a feedback loop to the other layers to help improve future predictions.
   

The Implementation.

AI Implementation Process

Here we illustrate the general flow chart of machine learning. The order of events and how data flows between the various stages is depicted.

Many processes are iterative and act as feedback loops to another process. Hence the term “learning” as the system learns from mistakes and improves its predictions over time.

CONTACT US