A comprehensive ML library that unifies the entire ML pipeline
Project description
SBYB - Step-By-Your-Byte
A comprehensive machine learning library that unifies the entire ML pipeline.
Overview
SBYB (Step-By-Your-Byte) is a Python library designed to provide a unified, offline-capable machine learning toolkit that outperforms existing solutions like TensorFlow and Keras. It integrates the entire ML pipeline from data preprocessing to model deployment in a single, cohesive package.
Key Features
- Unified Data Preprocessing: Automatic handling of missing values, outliers, encoding, and scaling
- Task Type & Data Type Auto-detection: Intelligent identification of ML tasks and data characteristics
- AutoML Engine: Automated model selection, hyperparameter tuning, and ensemble creation
- Evaluation & Explainability: Comprehensive metrics and model interpretation tools
- Deployment & Serving: Easy model export and deployment options
- Zero-code UI Generation: Automatic creation of user interfaces for models
- Project Scaffolding: Quick setup of new ML projects with best practices
- EDA Tools: Powerful data profiling and visualization capabilities
- Plugin System: Extensible architecture for custom components
- Local Experiment Tracking: Track, compare, and visualize ML experiments
- CLI & Programmatic API: Multiple interfaces for different workflows
Installation
pip install sbyb
Quick Start
Using the CLI
# Create a new project
sbyb project create --name my_project --template classification
# Run AutoML on a dataset
sbyb automl run --data data.csv --target target_column
# Generate a UI for a model
sbyb ui generate --model model.pkl --output ui_app
Using the API
from sbyb.api import SBYB
# Initialize SBYB
sbyb = SBYB()
# Preprocess data
import pandas as pd
data = pd.read_csv("data.csv")
preprocessed_data = sbyb.preprocess_data(data)
# Run AutoML
result = sbyb.run_automl(
data=preprocessed_data,
target="target_column",
output_dir="output"
)
# Generate UI
sbyb.generate_ui(
model=result.model,
output_dir="ui_app",
ui_type="dashboard",
framework="streamlit"
)
Documentation
For detailed documentation, visit https://sbyb.readthedocs.io/
License
MIT License
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