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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf StudyVideo and Text Based

Courses and Certificate Fees

Certificate Availability
no

The Syllabus

  • What is Machine Learning (ML) ?
  • ML and Finance; not ML for Finance
  • Classical Machine Learning: Introduction
  • Supervised Learning
  • Our first predictor
  • Notational conventions

  • Linear Regression
  • The Recipe for Machine Learning
  • The Regression Loss Function
  • Bias and Variance

  • Data Transformations: Introduction and mechanics
  • Logistic Regression
  • Non-numeric variables: text, images
  • Multinomial Classification
  • The Classification Loss Function

  • Baseline model
  • The Dummy Variable Trap
  • Transformations
  • Loss functions: mathematics

  • Entropy, Cross Entropy, KL Divergence
  • Decision Trees
  • Naive Bayes
  • Ensembles
  • Feature Importance

  • Support Vector Classifiers
  • Gradient Descent
  • Interpretation: Linear Models

  • Unsupervised Learning
  • Dimensionality Reduction
  • Clustering
  • Principal Components
  • Pseudo Matrix Factorization: preview of Deep Learning

Instructors

Articles

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