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Nixtla

Forecast using TimeGPT

Nixtla offers a collection of classes and methods to interact with the API of TimeGPT.

🕰️ TimeGPT: Revolutionizing Time-Series Analysis

Developed by Nixtla, TimeGPT is a cutting-edge generative pre-trained transformer model dedicated to prediction tasks. 🚀 By leveraging the most extensive dataset ever – financial, weather, energy, and sales data – TimeGPT brings unparalleled time-series analysis right to your terminal! 👩‍💻👨‍💻

In seconds, TimeGPT can discern complex patterns and predict future data points, transforming the landscape of data science and predictive analytics.

⚙️ Fine-Tuning: For Precision Prediction

In addition to its core capabilities, TimeGPT supports fine-tuning, enhancing its specialization for specific prediction tasks. 🎯 This feature is like training a machine learning model on a targeted data subset to improve its task-specific performance, making TimeGPT an even more versatile tool for your predictive needs.

🔄 Nixtla: Your Gateway to TimeGPT

With Nixtla, you can easily interact with TimeGPT through simple API calls, making the power of TimeGPT readily accessible in your projects.

💻 Installation

Get Nixtla up and running with a simple pip command:

pip install nixtla>=0.1.0

🎈 Quick Start

Get started with TimeGPT now:

df = pd.read_csv('https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/electricity-short.csv')

from nixtla import NixtlaClient
nixtla = NixtlaClient(
    # defaults to os.environ.get("NIXTLA_API_KEY")
    api_key = 'my_api_key_provided_by_nixtla'
)
fcst_df = nixtla.forecast(df, h=24, level=[80, 90])