Artificial Intelligence

Artificial Intelligence

1. Machine Learning (ML)

   • ML is the study of computer algorithms that can improve automatically through experience and by the use of data
     • Model built upon "Training Data"
   • Approaches
     • Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs
     • nsupervised learning algorithms take a set of data that contains only inputs, and find structure in the data, like grouping or clustering of data points.
     • Semi-supervised learning falls between unsupervised learning (without any labeled training data) and supervised learning (with completely labeled training data). Some of the training examples are missing training labels,
   • Relates by computational linguistics and the creation of informatic nodeds
   • Main application of ML is the ACI

2. Natural Learning Processing (NLP)

   • Refers to the branch of computer science—and more specifically, the branch of artificial intelligence or AI—concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.
   • Both are based on basic human skills, listening and understanding, or seeing and understanding.
     • Based on human senses

3. Computer Vision (CV)

   • Refers to the field that studies how machines can gain knowledge and understanding, through digital images or videos

4. Artificial classification intelligence (ACI)

   • Classification is a systematic grouping of observations into categories, such as when biologists categorize plants, animals, and other lifeforms into different taxonomies. It is one of the primary uses of data science and machine learning.
     • Data Science
       • is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data,[1][2] and apply knowledge and actionable insights from data across a broad range of application domains
       • Branch
       • Data mining
         • Is a process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
   • Type of A.I

5. Statistics

   • Regression Analysis
     • Regression analysis is a field of statistics. It is a tool to show the relationship between the inputs and the outputs of a system. There are different ways to do this. Better curve fitting usually needs more complex calculations.
   • Cluster Analysis
     • is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).
     • Basically grouping sets of data