IT Art Integrated Learning Project

 

Integration with Mathematics

 

What is linear algebra? 

Linear algebra is a branch of mathematics that deals with linear equations and linear functions which are represented through matrices and vectors. 

Why do I need to study linear algebra for machine learning?

Linear algebra is the building block of machine learning and 
deep learning. Understanding these concepts at the vector and 
matrix level deepens your understanding and widens your 
perspective of a particular ML problem.
 Here are a few applications of linear algebra in machine 
learning:
1. Vectorization 
2. Dimensionality Reduction 
3. Computer Vision

What is Optimization?

Optimization is the process of setting decision variable values in such a way that the objective in question is optimized. Optimization plays an important part in machine learning project in addition to fitting the learning algorithm on the training dataset. 

Why is optimization important in machine learning

Machine learning involves using an algorithm to learn and generalize from historical data in order to make predictions on new data.This problem can be described as approximating a function that maps examples of inputs to examples of outputs. Approximating a function can be solved by framing the problem as function optimization. This is where a machine learning algorithm defines a mapping function and an optimization algorithm is used to fund the values.

 

What is Probability?

 Probability theory allows us to make uncertain statements and reason in the presence of uncertainty

 

Probability in Artificial Intelligence (AI) 

 

AI Subjects or fields can be categorized as Learning, Problem Solving, Uncertainty & Reasoning, Knowledge,Representation and Communication.

Integration with science

 What are Neural Networks?

Neural networks are computing systems with interconnected  nodes that work much like neurons in the human brain. Using algorithms, they can recognize hidden patterns and correlations  in raw data, cluster and classify it, and – over time –  continuously learn and improve. Neural networks are designed to work like the human brain does.

 

Application of neural network

• Character Recognition - Neural networks can be used to recognize handwritten characters.

• Stock Market Prediction - Since neural networks can examine a lot of information quickly and sort it all out, they can be used to predict stock prices. 

• Medicine, Electronic Nose, Security and Loan Applications -These are some applications that are in their proof-of-concept stage, with the exception of a neural network that will decide whether or not to grant a loan, something that has already been used more successfully than many humans.

Neural networks can be used to create realistic pictures from line sketches -

 

Integration with social science

History of AI

Integration with art

Integration with English

Poem on AI

Artificially stimulated computers, that always strive to be better. An outstanding intellect they lead, only to fulfill us human's needs. They make daily life less tough, Activities and tasks don't seem rough. A.I. has become the new revolution, Coming up with amazing innovations. Smart machines will make your day, Navigation helps you find the way. Interactive tricks for the disabled, Making efficient plans or timetables. Bring humanity together to live in light, to ensure a future smooth and bright. A.I., one of humans best creations, A reality that was once pure fiction.