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Every part of machine learning your course covers.

Classical ML

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Deep learning

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  • RNNs and transformers
  • Transfer learning
  • PyTorch training loops

Methodology

  • Train / validation / test splits
  • Cross-validation
  • Hyperparameter tuning
  • Error analysis

Applied

  • NLP and text classification
  • Recommender systems
  • Forecasting
  • Kaggle-style projects
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01The brief
Machine LearningMastersDue in 7 days

Predict customer churn and explain it

Train and compare logistic regression and gradient boosting on a churn dataset. Handle class imbalance, report ROC-AUC with 5-fold cross-validation and explain the top features.

Requirements
  • Preprocessing with no leakage
  • Two models, 5-fold stratified CV
  • Class imbalance handled
  • Feature importance discussion
02The solution
churn.py14 lines
1prep = ColumnTransformer([
2 ("num", StandardScaler(), NUMERIC),
3 ("cat", OneHotEncoder(handle_unknown="ignore", sparse_output=False), CATEGORICAL),
4])
5
6# preprocessing lives inside the pipeline, so CV folds never leak
7model = Pipeline([
8 ("prep", prep),
9 ("clf", HistGradientBoostingClassifier(class_weight="balanced")),
10])
11
12cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)
13auc = cross_val_score(model, X, y, cv=cv, scoring="roc_auc")
14print(f"ROC-AUC: {auc.mean():.3f} ± {auc.std():.3f}")
notebook runs end to end · seed 42
03The explanation doc
explanation.pdf
1.
No leakage
Scaling and encoding are fitted inside each fold, never on the full dataset.
2.
Imbalance
class_weight="balanced" reweights the 18% churners instead of throwing data away.
3.
Results
Gradient boosting reaches 0.871 ROC-AUC against 0.842 for logistic regression.
04The price
AI predicted budget
$150–$280
Level · MastersAdvanced
Deadline · 7 daysStandard
Shown before any contact details were shared.
Final price from our team
$210
Delivered 1 day early
How it works

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Typical orders

Common machine learning assignments and typical budgets.

scikit-learn classification or regression
$100–$220
Usually 2–4 days
typical range
PyTorch deep learning project
$180–$420
Usually 4–7 days
typical range
NLP / text classification
$150–$350
Usually 4–6 days
typical range
Paper reproduction
$300–$700
Usually 7–14 days
typical range

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