Machine Learning 401 : Zero to Mastery Machine Learning

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Machine Learning 401 : Zero to Mastery Machine Learning

Learn Machine Learning Master Level, Deep Learning, Reinforcement Learning, Application of Machine Learning
What you’ll learn
  • Introduction to machine learning.
  • Linear prediction
  • Maximum likelihood and linear prediction
  • Ridge, nonlinear regression with basis functions and Cross-validation
  • Bayesian learning
  • Gaussian processes for nonlinear regression
  • Bayesian optimization, Thompson sampling and bandits
  • Decision trees
  • Random forests
  • Spring break
  • Random forests applications
  • Unconstrained optimization
  • Gradient descent and Newton’s method
  • Logistic regression, IRLS and importance sampling
  • Neural networks
  • Deep learning
  • Importance sampling and MCMC
  • Constrained optimization, Lagrangians and duality
  • Application to penalized maximum likelihood and Lasso
  • Deep Learning
  • Reinforcement Learning


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