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ML boot camp
Bayesian models
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ML boot camp
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01 Introduction
01 Introduction
Data is eating the world
What is AI
State of the art in AI
Bottlenecks for AI
02 Data engineering
02 Data engineering
Basic data engineering
Data format
š Practice
03 Big data
03 Big data
Context
Data processing history
Storing data at scale
Transforming data at scale
Databases types (SQL / NoSQL)
Case study: digital transformation
04 Data visualization
04 Data visualization
Fundamentals
Plots
Exploratory data analysis
š Practice
05 Regression
05 Regression
š Practice
06 Classification
06 Classification
š Practice
07 Models panorama
07 Models panorama
Models properties
Ensemble learning & tree-based models
Support vector machines
Bayesian models
08 Model selection
08 Model selection
Cross validation
Hyperparameter tuning
š Practice
09 Neural networks
09 Neural networks
10 Tutorials
10 Tutorials
š Practice nĀ°1: data engineering
š Practice nĀ°1: data engineering (students version)
š Practice nĀ°2: exploratory data analysis
š Practice nĀ°2: exploratory data analysis (students version)
š Practice nĀ°3: regression
š Practice nĀ°3: regression (students version)
š Practice nĀ°4: classification
š Practice nĀ°4: classification (students version)
š Practice nĀ°5: cross validation & hyperparameter tuning
š Practice nĀ°5: cross validation & hyperparameter tuning (students version)
Bayesian models