Data Science for Beginners

Are you wondering what’s all this buzz about data science? The following videos will give you a good introduction to data science.

Use the links below to go to each video:

Problems solved by data science
Data Quality
Question/Problem Quality
Example of linear regression model

Problems solved by data science

The first video is about the five questions/problems that data science can answer.

Question	Problem	Example
Is this A or B or C?	Classification	Will this customer leave or not?
Is this weird?	Anomaly detection	Is this transaction typical when compared to other transactions from this credit card?
How much/many?	Regression	What will be the sales for the following six months?
How is this organized?	Clustering	What are the groups of similar customers in this marketing database
What should I do next?	Reinforcement learning	In a self-driven car should I stop or accelerate if I see a yellow light.

Data Quality

To have good data science models, data should be:

Relevant to the problem you’re solving
Connected (with the least number of missing values as possible)
Accurate (with low bias)
Enough to work with

Problem Quality

Try to make the questions as precise as possible and to have adequate data for the problem you’re solving. For example, if your question is: what are going to be the sales for the next six months?, then you should have historical sales data.

Example of linear regression model

In this video you’ll see how to make predictions of diamonds price based on the carats of them using a simple linear regression model.

Getting Started With Azure Machine Learning

One possible way of getting started in data science is to explore existing solutions to data science problems. The following video explains how to use existing solutions in Azure Machine Learning.

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Orlando Mezquita

Love helping out people to get better using data analysis tools! My day job is statistician for a Pharmaceutical Company.