Mar 10, 2023 · Let's discuss in detail how to do refactoring related to ML code. Contents: Understanding OOP in Python; Refactoring patterns; ML Model-Normal code and refactored code;...

Use Docker and stop hearing "Works on my machine!" Clean code practices (from Clean Code and Refactoring) adapted for machine learning / data science workflows in Python. This is not a style guide. It's a guide to producing readable, reusable, and refactorable software.

Jun 25, 2021 · A model can have many kinds of improvement: shorter code, cleaner code, more pythonic code, faster predictions, easier to use, more readable, more interpretable, dimensionality reduction, faster training… you get the idea.

Feb 23, 2025 · Inspired by previous work that leverages commit messages to detect refactoring, we introduce MLRefScanner, a prototype tool that applies ML techniques to detect refactoring commits in ML Python projects.

The refactoring cycle: The instructions for how to run each step can be found in the refactoring exercise. Create a Python module and define a function. Move existing implementation from notebook into that function. git add . When refactoring, don't change the program's observable behaviour. (Remember the Two Hats) Keep tests in watch mode.

In 11 videos, you will learn the steps involved in designing ML algorithms. The complexity in the algorithm is huge, and learners will observe how to write iterative and incremental code, and how to apply refactoring to it.

Apr 14, 2025 · This study explores Graph Neural Networks (GNNs) as a transformative tool for code refactoring, using abstract syntax trees (ASTs) to boost software maintainability. It analyzes a dataset of 2 million snippets from CodeSearchNet and a custom 75000-file GitHub Python corpus, comparing GNNs against rule-based SonarQube and decision trees. Metrics include cyclomatic complexity (target below 10 ...

5 days ago · Refactor Python code for better modularity and add functionality. You can query a model directly and test the results returned when using different parameter values with the Cloud...

6 days ago · Leveraging AI for code quality enhancement introduces a transformative approach that combines traditional methods with advanced machine learning techniques. This section explores how AI can significantly improve Python code quality through various strategies and …

Feb 6, 2022 · MLP1 can then be refactored into: layers.append(nn.Linear(in_features, out_features)) self.layers = nn.ModuleList(layers) def forward(self, x: torch.FloatTensor) -> torch.FloatTensor: rv = x for layer in self.layers: rv = layer(rv) rv = F.relu(rv) return rv. The application of F.relu in forward() is suspect for a few reasons: