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#13 of 36

chloe-dl

Level 4 · Proficient · Title: Modeler

4,860 XP

140 XP to the next level

Completed branches

48/ 228

Mastered sub-branches

165/ 680

Milestone projects

1/ 15

Highest tier

N3Classical machine learning

Specialties

Still on the common trunk: specialties open from tier N6.

Their curriculum, tier by tier

A completed branch lights up in its family's colour. A branch is available once all its prerequisites, milestone projects included, are completed.

  • Completed
  • Available
  • Locked
  1. N0Computing and PythonScripter15/15
    • Python basics (Completed)
    • Git (Completed)
    • Linux / Shell (Completed)
    • SQL (Completed)
    • OOP (Completed)
    • Iterators & generators (Completed)
    • Typing (Completed)
    • NumPy (Completed)
    • Tests (Completed)
    • Pandas / Polars (Completed)
    • SciPy (Completed)
    • Visualization (Completed)
    • Profiling (Completed)
    • Parallelism (Completed)
    • GPU computing (Completed)
  2. N1Mathematics of AIAnalyst12/12
    • Linear algebra (Completed)
    • Calculus (Completed)
    • Probability (Completed)
    • Eigenvalues (Completed)
    • Gradient, Jacobian, Hessian (Completed)
    • Bayes (Completed)
    • Information theory (Completed)
    • Statistics (Completed)
    • SVD & decompositions (Completed)
    • Optimization (Completed)
    • MLE / MAP (Completed)
    • Gradient descent (Completed)
  3. N2Foundations of learningStatistician12/12
    • Supervised learning (Completed)
    • Unsupervised learning (Completed)
    • Bias / Variance (Completed)
    • Validation (Completed)
    • Semi & weakly-supervised (Completed)
    • Self-supervised (Completed)
    • Online & active learning (Completed)
    • Transfer & multi-task (Completed)
    • Regularization (Completed)
    • Metrics (Completed)
    • Distribution shift (Completed)
    • Calibration & uncertainty (Completed)

    Milestone 1 · mandatory projects

    • Statistical engine in pure NumPy (Completed)
  4. N3Classical machine learningModeler9/17
    • Regression (Completed)
    • Decision trees (Completed)
    • k-NN (Completed)
    • Naive Bayes / LDA / QDA (Completed)
    • Clustering (Completed)
    • Dimensionality reduction (Completed)
    • Bayesian models (Completed)
    • Graphical models (Completed)
    • Penalized regression (Completed)
    • Logistic regression (Available)
    • Bagging & forests (Available)
    • Boosting (Available)
    • Gaussian Mixture & EM (Available)
    • Manifold learning (Available)
    • Anomaly detection (Available)
    • SVM (Locked)
    • Stacking & voting (Locked)
  5. Tiers N4 to N13 · still locked
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