What is Machine Learning?

What is Machine Learning?

Village - 600 houses - 2000 people
Grocery - City Centre - 10 kms

Problem Statement - To buy groceries, villagers had to go 10 kms from village.

Ganesh went to city centre - 50 items -
200 pieces of 50 items -
It generally takes 2 days time. On 3rd day he will receive the items.

5-6 days - 200 pieces of each item got exhausted
It generally takes 2 days time. On 3rd day he will receive the items.
2-3 days the grocery shop had no item to sell.
This pattern ganesh observed for 2-3 weeks.

Observation and action taken - He started giving the order to the wholesaler 3 days in advance. He started giving order to wholesaler when he exhuasted 70% of his stock.
There was no idle period. Ganesh had 50 items always available in his shop.

Problem Solved -
Tea Powder -
The washing shop -
The shampoo -

Went back to villagres and asked for feedback -
have 50 items in the shop
30 new items from villagers -
80 items -

few months the shop was stable -
The weekly market was decided on thursday -
Started facing the issue of human workers -
Also the items he bought also were not sufficient to solve the weekly market demand

Observed this for 2 weeks -
On thursday, he will keep 3 more people ready to serve buyers in the shop and for thursday, he will buy 100 items each -
80 items - 100 pieces
he gave order on Sunday for weekly market

and for daily needs he was giving order when 70% of his stock exhausted

Shop became stable - problem solved

Due to increasing demand - Ganesh started facing the stock issue and the humaun resources issue

Let's open the Village Groceries Centre - Bigger space, more people to work and more pieces of 80 items

1 room 15*15
100*100
3 human resources - 9 human resources
500 pieces for all his needs
Ganesh - Machine Learning System
Data - Grocery Items -
Villagers feedback - Feedback to the ML model

Machine Learning is the computer system or application which learns from past data, improves with feedback and makes better decisions based on patters observed.
Initial data - Training data
Pattern Observed - Wholesaler taking 2 days time to deliver the order
Result - ML model started giving recommondation to place the order to wholesaler 3 days in advance
ML Application Became stable
Feedback from villagers - Feedback to ML model
Retrained the Model - 80 items
Stable -
Pattern - Huge demands on thursday
Result - Recommendation that the stock for Thursday weekly market should be bought on Sunday
Stable -
Pattern - Demand Increase
Recommendation - To start the Village Groceries Centre - Bigger space, more people to work and more pieces of 80 items

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