In short, artificial intelligence is a broad concept of machines capable of performing tasks in a way that we call it “smart,” and machine learning is a current application of artificial intelligence based on the idea of ”creating the ability for machines to Access to information and self-learning permission “.
Making codes which give machines the ability to think like human beings so that they just have to connect them to the data warehouse to access all the available information and start learning and clustering a tremendous transformation in various industries like Automotive and …
A “neural network” is a computer system designed to cluster information in the same way that the human brain works. Using the “Neural Network”, you can teach computers, for example, how to identify images and classify them according to the elements in them. Essentially, the “neural network” works on a probabilistic system, and can provide a degree of assurance based on the information it provides, comment, decision or prediction.
Today, artificial intelligence and machine learning, in particular, have interesting suggestions for transforming our world. With the promises made by both of them, automating repetitive tasks, as well as providing innovative Creative Insights for companies, all industries from banking to medical care and manufacturing are exploiting the benefits of these two developments.
Machine learning applications are capable of reading text and interpreting whether the author is, for example, dissatisfied or satisfied. They can also listen to a piece of music that they are interested in, and make a happy or sad music comment, and, on that basis, offer other pieces of music that match the mood of the person. In some cases, they can even inspire a piece of music, they themselves are the creator of a music that expresses the theme of happiness or sadness, or at least they know that this piece of music will be welcomed by fans of the original piece.
In drilling operation projects, the advanced methods of machine learning for clustering and predicting can be used because of the large volume of offset wells data. Neural network and artificial intelligence methods can be used to predict ROP accurately, and clustering methods can be used to classify existing data into different groups and use them for future wells with the same conditions.