Workshop by Navya Prakash
10/12/19 - Link to repo
Data Science (Extract and making human sense)
- Domain Expertise
 - Statistics
 - Coding
 
Roles
- Data Analys
 - Data Engineer
 - Data Scienctist
 - Data Architect
 - Developer
 
11/12/19 - Link to repo
80% spent cleaning and prep data
if age, median > mean then more on the higher side
What is Machine Learning? -automates data extrapolation and classification
Prediction
- linear regression
 
Classification
- logistic regression
 - decision tree
 
Predictive & Preemptive Analytics
- self sustain algo
 
As a person, we have gathering data all the time
Predictive ML model
- clean
 - filter
 - build
 - train
 - test
 
Type of ML
- supervised learning
 - unsupervised learning (groupings, recommendation)
 
could platform
- Quick and affordable
 - repeated use
 
Microsoft Azure ML algo cheat sheet
julia(like python but faster), R
12/12/19 - Link to repo
split different routes for GET and POST so no duplicate request if refresh
2 components
- the tranlation (AI to translate)
 - which part of the image (AI to retrieve the text)
 
api
- breaks if more than 10 people
 - can adjust threshold
 
check out
- azure cognitive services apis
 - how-old.net
 - what-dog.net (broken)
 - microsoft learn labs
 
AI ethics
- AI data and privacy considerations (public info are plaintext, critical data must be encrypted)
 
how data is stored, belong to group (what is the size of groups, legal restrictions varies)