Machine learning in Python – extended version

Machine learning in Python - extended version

Training description

Machine Learning changes the business reality rapidly. Solutions that is being built based on data, may support the decision-making process.

“Machine Learning in Python”  is an advanced training on building predictive analytics in Python.

Duration: 4 days 8 hours each (including an hour lunch break)

Requirements: knowledge of Python programming language at an intermediate level which can be acquired during our training “Introduction to Python”.

Training agenda

Part one: Let’s get it started!

  • What’s Machine Learning?
  • Algorithm distinction
  • Machine Learning workflow

Part two: The necessary foundation

  • Training data vs.Test data
  • Exploratory Data Analysis
  • Feature selection/extraction
  • Overfitting
  • Model validation

Part three: Overview of algorithms

  • Statistical modeling recap (linear regression, logistic regression)
  • Decision trees
  • SVM
  • Ensemble methods
    • Random Forest
    • Boosting

Part four: Let’s group the world!

  • Clustering methods
    • K-means
    • Hierarchical clustering
    • DBSCAN
    • Fuzzy clustering
    • Affinity Propagation

Part five: In search of best solution…

  • Dimensionality reduction techniques
  • Regularization
  • Hyperparameter tuning
  • Black-box model interpretability

Contact us about closed training

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