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The goal of most ML projects is to create a model to perform certain functions, such as
BRAINY classifying text, predicting house prices, or identifying emotions. In the deep learning model,
FACT this is achieved through a neural network, where the layers of the neural network use matrix and
vector multiplication to adjust parameters.
AI REBOOT
Answer the following questions:
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1. If A = 1 B = [1 5 7] Find AB.
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2. Raju, Charu, Shelly are the students of 12th class. Raju has 15 books and 6 pens, Charu has 10 books and 2
pens and Shelly has 13 books and 5 pens. Express this in matrix form.
3. Find the cross product of vectors a = i + 2j + k and b = i + 3j + 4k.
4. Find the sum of the vectors a = i – 2j + k and b = –2i + 4j + 5k.
Context Setting
Context setting means giving background information that helps understand a topic clearly. It is the practice of
applying specific conditions or parameters to make data meaningful. It connects what you already know with what
you are going to learn.
Context setting involves the following elements:
u Filtering with selection: Choosing only the needed data from a table.
u Importance of schema understanding: Knowing the table structure helps us join and read data correctly.
Example: Suppose one table has students’ names and another has marks. By selecting only, the needed columns and
joining them, we can show each student’s marks beside their name.
How Context Works with Set Operations?
Set operations help us combine or compare data, similar to mathematical sets. They are grouped into two types:
Binary Operations (Union, Intersection, Difference):
These operations work on two tables at a time.
u Union combines rows from both tables.
u Intersection shows only common rows.
u Difference shows rows present in one table but not in the other.
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