GIC East Africa

Artificial Intelligence And Machine Learning

Artificial Intelligence (AI) is the study of computer science methods that are used to create intelligent machines. Machine Learning, on the other hand, refers to a method or type for automated data analysis that employs statistical models based upon algorithms rather than human-crafted rules like decision trees do where each node represents an experimental experiment with an input value of one and its corresponding output probability whereas in AI there may be many different inputs all producing different outputs, so you’d have this massive database of data that would provide us with more information about how things work internally.

Artificial intelligence refers to a machine’s capability to solve problems that are often done by machines or intelligent humans. AI allows machines and robots to perform jobs “smartly”. This is achieved through mimicking human capabilities, such as understanding data and reasoning with the data to enable the robot/computer program to do certain tasks better than the human race. They can also assist them to get through instructions without having request assistance.

Artificial Intelligence: Its Benefits

Artificial intelligence’s future is in sight as an electronic system with human-like abilities. It can speak any accent or language, in the event that there is enough data online.

AI is the way of the future. It’s being used everywhere to aid us today, from retail stores and healthcare fields up through finance departments for fraud detection whatever you want! The technology is capable of doing anything if it is used appropriately. I’m sure you already feel more informed due to its capabilities.

Machine Learning Process

Machine learning is a field of study that aims to improve the intelligence of computers by teaching them through experience. It is accomplished through algorithms, which provide the computer with examples or programs that explain what they should do when presented with new information, such as drawing conclusions based on input data for this passage on trade-offs between quality control and cost efficiency. The machine learns from its mistakes until it is able to draw the correct conclusion , with no any human intervention.

Today, machine learning and artificial Intelligence are applied to all kinds of technological devices. Examples are CT scanners, MRI’s and automobile navigation systems. You can use this data to feed your program feedback. This will enable the system to understand from the user how they behave and interact in specific situations. In this way, when we design our algorithms there’ll be more sensitive about whether their choices were right Based on the previous input.

Artificial Intelligence refers to the technology of creating intelligent machines that are human-like in their capabilities for reasoning and problem solving. This allows AI-powered smartphones or computers to learn from data without the need for explicit programming or instruction. Instead, these technology heavily depend on deep learning as well as machine learning. It will bring us future benefits such as high-performance computing.

To learn more, click udacity deep learning nanodegree review