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GitHub / datstat-consulting / DeepLearningEconometrics
Implementing standard econometric models using Stochastic Gradient Descent and Perceptrons instead of MLE and GMM.
Stars: 2
Forks: 0
Open Issues: 0
License: mit
Language: Python
Repo Size: 233 KB
Dependencies:
4
Created: about 1 year ago
Updated: 4 months ago
Last pushed: 4 months ago
Last synced: 4 months ago
Commit Stats
Commits: 81
Authors: 1
Mean commits per author: 81.0
Development Distribution Score: 0.0
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/datstat-consulting/DeepLearningEconometrics
Topics: causal-inference, econometrics, economics, economics-models, impact-analysis, impact-evaluation, machine-learning, machine-learning-algorithms, perceptron, perceptron-algorithm, perceptron-learning-algorithm, perceptron-neural-networks, randomized-controlled-trials, time-series, time-series-analysis
Files
Dependencies
- matplotlib *
- pandas *
- plotly *
- torch *