Predicting what group or label a sample belongs to.
- Is this email spam or not spam?
- Is this behavior usual or abnormal?
- Is this a cat or a dog?
Predict a numerical value of interest.
- How many points will this team score tonight?
- What will the temperature be?
- What is this stock’s price?
- Credit scores
Find other samples (from a larger dataset) that are similar to what you are seeing
- Similar gene sequences
- Similar profiles for online dating
- Previous patent searches
- Carpool matching
Grouping samples together based on their similarity
Data Analytics can be divided into 4 main sections:
Descriptive, Diagnostic, Predictive, and Prescriptive.
1) Descriptive Analytics: tells you what’s happened in the past
2) Diagnostic Analytics: helps you understand why something happened in the past
3) Predictive Analytics: predicts what is most likely to happen in the future
4) Prescriptive Analytics: recommends actions you can take to affect outcomes
🦠 Here’s an example: I’m trying to get hand sanitizer during the pandemic.
Descriptive analytics would tell me that from March 15th - April 15th, 89% of stores ran out of their sanitizer supply.
Diagnostic analytics would tell me they ran out because there was an enormous spike in hygiene and germ spreading due to the outbreak of #CoronaVirus
Predictive analytics would predict the likelihood of my nearest grocery store having sanitizer in stock.
Prescriptive analytics would recommend a time, place, and plan to obtain the needed sanitizer.
Data Science Crash Course
Broad topics: 1) What questions can data science solve? How is it used? 2) Where does data exist? What type of data? 3) How do we get the data? 4) Prep / cleaning 5) Understanding the data: EDA + Viz 6) Predictive models 7) Deployment
Evaluate what a career in data science might look like, and how to get there.
What are the different aspects of data science? BI Machine learning AI
What is Descriptive What is Predictive
Vocabulary of data science