DrivenData Labs

MAY 24, 2023

Several additional approaches were attempted but deprioritized or entirely eliminated from the final workflow due to lack of positive impact on the validation MAE. What are some other things you tried that didn't necessarily make it into the final workflow?

Machine Learning 225

Machine Learning Machine Learning Data Science Decision Trees 225

Pickl AI

NOVEMBER 28, 2024

Key concepts include: Cross-validation Cross-validation splits the data into multiple subsets and trains the model on different combinations, ensuring that the evaluation is robust and the model doesn’t overfit to a specific dataset. Scalability Considerations Scalability is a key concern in model deployment.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 12, 2024

Python supports diverse model validation and evaluation techniques, which are crucial for optimising model accuracy and generalisation. Cross-validation Cross-validation partitions data into training and validation sets multiple times to assess model performance across different subsets.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

DagsHub

APRIL 21, 2024

It also provides tools for model evaluation , including cross-validation, hyperparameter tuning, and metrics such as accuracy, precision, recall, and F1-score. Azure ML offers automated machine learning capabilities, allowing users to quickly build and deploy machine learning models without extensive manual tuning or coding.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Mlearning.ai

JUNE 28, 2023

The compare_models() function trains all available models in the PyCaret library and evaluates their performance using cross-validation, providing a simple way to select the best-performing model. Detailed guides on deploying models to the cloud can be found in the official PyCaret documentation.

Machine Learning 52

Machine Learning Machine Learning Data Preparation Data Science 52

Pickl AI

NOVEMBER 18, 2024

Cross-Validation: Instead of using a single train-test split, cross-validation involves dividing the data into multiple folds and training the model on each fold. Finding the best combination of these parameters can significantly enhance model performance.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

SEPTEMBER 18, 2024

You should be comfortable with cross-validation, hyperparameter tuning, and model evaluation metrics (e.g., Algorithm and Model Development Understanding various Machine Learning algorithms—such as regression , classification , clustering , and neural networks —is fundamental. accuracy, precision, recall, F1-score).

Machine Learning 52

Machine Learning Machine Learning Algorithm Natural Language Processing 52