Intro to DataScience

Question 1

What is structured data?

Answer 1

Data that is recorded within a spreadsheet, has data, tables etc

Question 2

What is unstructured data?

Answer 2

Data like twitter, images, newspapers, and stuff that doesn’t necessarily have a data structure

Question 3

What kind of data structure is email?

Answer 3

Most likely structured, to, from, content, time, etc. The only unstructured part is the actual writing of content

Question 4

Data science is interdisciplinary

Answer 4

Programming/ coding, math and stats, business logic, statistical methods, math and algorithms

Question 5

Data Analytics

Answer 5

Analyzing big data - based on history - RAW DATA BEING USED TO TO DERIVE MEANINGFUL INFORMATION (MEAN MEDIAN AND MODE)

Question 6

Data Science

Answer 6

Can analyze future DEALS WITH THE FUTURE – uses data from data analytics to process information and predict

Question 7

Machine Learning

Answer 7

distance based, regression algo’s and also deep learning

Question 8

Deep learning

Answer 8

Works with deep neural networks

Question 9

AI

Question 10

Data science is interdisciplinary.

Answer 10

Programming/ coding, math, and stats, business logic, statistical methods, math, and algorithms

Question 11

Big Data, 4 V’S OF BIG DATA

Answer 11

With too much data to fit into a machine, high volume (amount) and velocity (how fast, aka tweets 150000 per second), and or high variety (could be text, image), data is generated super quickly and veracity(data accurately represents reality) (, of information assets that demand cost-effective, innovative forms of information processing that enable insight, decision making, and process automation

Question 12

Descriptive analytics

Answer 12

What happened? eg. Starbucks sells 500 amount of coffee every day (deals with history)

Question 13

Diagnostic

Answer 13

Why did it happen? eg star only sold 2000 in a day, more than (was there an event nearby? free cup of coffe? good add?) – deals with history

Question 14

Predictive analytics

Answer 14

What will happen? we will sell this many Starbucks tomorrow, most likely

Question 15

Prescriptive analytics

Answer 15

What do we need to do? Can you write a formula so Starbucks sells 1500 a day?

Question 16

External data

Answer 16

finding external data (like why prices may change for houses) schools? stock market price, economy, neighborhood

Question 17

External data

Answer 17

Figure out algorithm error possibly because of like school ranking, stock market, etc

Question 18

internal data

Answer 18

gathering data from your own database in company

Question 19

except, exception, ValueError

Answer 19

except - catches all errors, exception - like catch error, tells you your error, ValueError, catches just the issue with the value