Ocean Protocol

NOVEMBER 28, 2024

Firepig refined predictions using detailed feature engineering and cross-validation. Yunus focused on building a robust data pipeline, merging historical and current-season data to create a comprehensive dataset. This structure ensured the model could adjust to unpredictable scenarios during the race.

Cross Validation 85

Cross Validation Data Scientist Decision Trees Data Science 85

Iguazio

JUNE 25, 2023

In some cases, cross-validation techniques like k-fold cross-validation or stratified sampling may be used to get more reliable estimates of performance. Consider performing this tuning within a cross-validation framework to avoid overfitting to a specific test set.

ML 52

ML ML Clustering Cross Validation 52

Pickl AI

DECEMBER 16, 2024

Split the Data: Divide your dataset into training, validation, and testing subsets to ensure robust evaluation. Fit the Model: Use the training data to fit your model while tuning hyperparameters for optimal performance. Deployment is crucial as it allows stakeholders to benefit from real-time insights generated by the model.

AI 52

AI AI Machine Learning Machine Learning 52

The MLOps Blog

DECEMBER 7, 2022

Knowing what needs to be done and in what order (the whole process and management side of data) is often overlooked , and we know sometimes keeping everyone up to date can be a bit tedious in its own way, but if you can orchestrate pipelines with dozens of steps in your sleep, you surely can take a moment to write what you’re up to, right?

ML 52

ML ML AWS ETL 52

DagsHub

MARCH 5, 2024

Utilization of existing libraries: Utilize package tools like sci-kit-learn in Python to effortlessly apply distinct data preparation steps for various datasets, particularly in cross-validation, preventing data leakage between folds.

Cross Validation 52

Cross Validation Algorithm Data Pipeline Data Preparation 52

Mlearning.ai

MARCH 15, 2023

I have checked the AWS S3 bucket and Snowflake tables for a couple of days and the Data pipeline is working as expected. The scope of this article is quite big, we will exercise the core steps of data science, let's get started… Project Layout Here are the high-level steps for this project.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 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. Pipeline Orchestration Tools To handle the end-to-end workflow orchestration, you can use famous tools like Apache Airflow and Kubeflow Pipelines.

Machine Learning 59

Machine Learning Machine Learning ML ML 59