According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.
Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think
AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.
We @ Infogen Labs work in Machine Learning and Deep Learning under AI
Machine learning is a subset of AI.
One aspect that separates machine learning from the knowledge
Machine learning is a subset of AI.
One aspect that separates machine learning from the knowledge graphs and expert systems is its ability to modify itself when exposed to more data; i.e. machine learning is dynamic
The machine will get evolve like a human, it can predict, classifies, clusters information more accurately if it is exposed to more data. Data is the heart of Machine Learning. In the ML process, data acquisition is the first step, followed by data preprocessing, model building and fine-tuning. @ Infogen we have worked on the different types of data and applied machine learning algorithm to achieve the objective. We have a team with data preparation capability, basic to the complex algorithm knowledge base, deployment capability
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Deep learning is getting lots of attention lately and for good reason. It’s achieving results that were not possible before.
In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound. Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance. Models are trained by using a large set of labeled data and neural network architectures that contain many layers.