General Flashcards

1
Q

What are the 9 key steps in the Data Science Process Workflow?

A
  1. Specify Objective
  2. Acquire Data
  3. Clean Data
  4. Explore Data
  5. Establish baseline model
  6. Model the Data
  7. Analyse Results
  8. Communicate findings
  9. Iterate -> 2.
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2
Q

What are the key questions to ask of recently acquired data?

A
What is relevant?
How was it sampled?
Where can we obtain the data?
How can we clean the data? 
Are there privacy issues?
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3
Q

What are the key questions to ask when exploring data?

A
Are there anomalies? 
Are there any Patterns?
How to deal with the missing data?
What does the data represent?
What features will be relevant ?
Can we construct new features?
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4
Q

What does it mean to Establish a baseline?

A

Create a simple baseline model/score that all future models are compared against.

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5
Q

What are the key steps in modelling data

A
Build a model
Fit the model 
Validate the model 
What assumptions are we making about the data?
Which types of models perform better?
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6
Q

What are the important steps when communicating findings

A

Restate the hypothesis, process, findings and analysis.

Ensure that results are reproducible

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7
Q

Key steps in Iterating a model

A

Continue to aquire more data
Create new features
Improve the current model

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8
Q

Key Data Science Deliverables

A
Prediction 
Forecasts 
Anomaly Detection
Recognition 
Optimisation 
Segmentation 
Recommendations
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9
Q

Prediction examples

A

Predicting is a borrower will repay on time or predicting who will win an election next year

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10
Q

Forecast examples

A

Forecasting future sales and demand, tomorrow’s weather

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11
Q

Anomaly detection

A

Detecting credit card fraud, money laundering etc

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12
Q

Optimisation examples

A

Minimise shipping costs

Finding optimal routes

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13
Q

Segmentation examples

A

Finding groups of similar customers to customize advertising, or detect high yield segments

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14
Q

Recognition examples

A

Recognise speech, text or images

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15
Q

Why is it important to establish a baseline

A

A baseline puts a more complex model into context

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