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)