The complete ML toolkit — EDA, cleaning, training, explainability, deployment
Project description
mlpilot 🚀
The complete machine learning toolkit that just works.
One import. One goal. No configuration.
The Vision
Most ML libraries require hours of setup, API keys, and complex boilerplate. mlpilot changes that. It is designed to be Zero-Config and Unbreakable, whether you are running on a powerful GPU server, a local laptop, or a free Google Colab notebook.
Quick Start (Truly Zero-Config)
Install the library:
pip install mlplt
Analyze your data in 3 lines (No API keys or setup needed):
import mlpilot as ml
import seaborn as sns
df = sns.load_dataset('titanic')
# Ask anything in plain English
ans = ml.analyst(df)
ans.ask("What was the survival rate by passenger class? Show a bar chart.", auto_run=True)
Key Modules
| Module | Description | Example |
|---|---|---|
| SmartEDA | Instant 12-section data analysis reports. | ml.analyze(df) |
| AutoCleaner | One-click missing value and outlier handling. | ml.clean(df) |
| FeatureForge | Leakage-safe automated feature engineering. | ml.features(df) |
| BaselineBlitz | Compare 5+ models in 10 seconds. | ml.baseline(X, y) |
| HyperX | Fast, budget-aware hyperparameter tuning. | ml.tune('lgbm', X, y) |
| AI Analyst | Natural language interface to your data. | ml.analyst(df).ask(...) |
| LaunchPad | Generate FastAPI + Docker deployments instantly. | ml.deploy(model) |
Why mlpilot?
- 📦 Zero-Config AI: Built-in local AI engine (Transformers) for when you don't have API keys.
- 🧹 Unbreakable Paths: Works perfectly regardless of your OS, drive letter, or notebook environment.
- 🤫 Professional Silence: No technical clutter. Just clean, actionable answers.
- 🛠️ Batteries Included: Everything from cleaning to deployment in a single package.
License
MIT © mlpilot contributors
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