Data Science activities

• Activities done in data science work, and how they typically occur
  • Problem formulation
  • Data acquisition
  • Data exploration
  • Analysis
  • Communication of results
  • Take action automatically
• Data and metadata
  • Data meaning, Data structure (schema), Provenance
• Ethics in data science work

python

data error (5B)

Data Cleaning - A process where the data scientist aims to get a dataset which has fixed the data quality problems in source data

logic data (6A)

ML (9A)

• Output of the training process is a computer system that includes a predictive model
• Supervised learning
• Train-validate-test
• Underfitting and overfitting
• K-nearest-neighbour regression
• Find the choice of one splitting attribute and thresholds that produces the “lowest impurity” division

11 A

• Clustering: k-means clustering
• Content-based