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Artificial Intelligence helps computers to understand and recognise patterns, much like how humans do. Just as
we learn to recognise patterns in different things we see or hear, AI can do the same with various types of data,
whether it’s numbers, images, or even speech and text. These patterns help AI to solve puzzles – like identifying
dogs and muffins, or predicting floods, earthquakes, etc.
Task #Problem Solving & Logical Reasoning
Let’s think and answer a few more!
1. Find out the middle value from the given numbers?
2, 5, 8, 11, 14
2. Fill in the missing number and find the next number in the given series?
3, 6, 12, 24, ___, 96, ___
3. Identify the highest temperature in the given graph and mention the time of it.
Temperature v/s Time
Temperature 50
45
40
35
30
6 am 10 am 2 am 6 am
Time
4. How many faces are there in a dice?
5. How many sides does a coin have?
6. What is the shape of a ball?
Essential Mathematics for AI
Math will help us to better understand AI and its way of working, but what kind of math is needed for AI?
The kind of math needed for AI includes:
1. Probability and Statistics (exploring data): Probability theory and statistics are key fundamentals for many
AI algorithms, particularly those involving machine learning. It is useful in tasks such as natural language
processing, computer vision, and decision-making.
2. Linear Algebra (finding out unknown or missing values): Linear algebra is involved in large-scale data
processing playing a vital role in machine learning and AI. It performs operations in neural networks, image
processing, and data transformations.
3. Calculus (training and improving AI model): Calculus is essential for understanding the best possible
solution algorithms used in machine learning. It minimise mistakes and maximise the parameters of machine
learning models.
4. Graph Theory: Graph theory is used in AI representing trends using data visualisation.
300 Touchpad Artificial Intelligence (Ver. 3.0)-IX

