Statistical Method Recommender

Handling Imbalanced Datasets in ML

Learn how to tackle imbalanced datasets in machine learning projects using Python. Explore resampling, ensemble techniques, cost-sensitive learning, and anomaly detection. Guide through the process with Python libraries and evaluation

Advanced Time Series Analysis and Forecasting in Python

Learn how to define objectives, assess data, select libraries (Prophet, Statsmodels, TensorFlow/PyTorch), techniques (ARIMA, SARIMA, LSTMs), rationale, implementation guidance, limitations, and build confidence in time series analysis and

High-Dimensional Data Analysis Guidance

Comprehensive guide on navigating high-dimensional data complexity through PCA, Factor Analysis, and Cluster Analysis, with tools, rationales, limitations, and confidence-building tips.

Advanced Statistical Methods for High-Dimensional Multivariate

Explore PCA, t-SNE, and Random Forests for non-linear relationships and dimensionality reduction in high-dimensional datasets using Python, guiding implementation and considering limitations.

Bayesian Hierarchical Modeling with PyMC3

Learn how to implement Bayesian hierarchical models with PyMC3 in Python, addressing complex dependencies in large datasets efficiently. Gain insights on model selection, implementation strategies, and considerations for enhancing model