https://github.com/shaheennabi/time-series-related-practices-and-mini-projects

ChatGPT 🎇 Time Series Forecasting Experiments 🎆 A collection of hands-on experiments with time series data 📊, featuring models like ARIMA, LSTM, and Prophet. 🚀 From data preprocessing to forecasting, explore real-world applications like stock predictions and weather forecasting 🌍. Continuously updated with new techniques and models for better
https://github.com/shaheennabi/time-series-related-practices-and-mini-projects

arima-forecasting autoarima sarimax sequence-to-sequence time-series-forecasting

Last synced: about 2 months ago
JSON representation

ChatGPT 🎇 Time Series Forecasting Experiments 🎆 A collection of hands-on experiments with time series data 📊, featuring models like ARIMA, LSTM, and Prophet. 🚀 From data preprocessing to forecasting, explore real-world applications like stock predictions and weather forecasting 🌍. Continuously updated with new techniques and models for better

• Host: GitHub
• URL: https://github.com/shaheennabi/time-series-related-practices-and-mini-projects
• Owner: shaheennabi
• License: mit
• Created: 2024-10-14T16:58:21.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-11-11T08:43:26.000Z (6 months ago)
• Last Synced: 2025-01-31T08:14:50.957Z (4 months ago)
• Topics: arima-forecasting, autoarima, sarimax, sequence-to-sequence, time-series-forecasting
• Homepage:
• Size: 5.86 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# 🚀 Time Series Data Experiments & Projects 🎇

Welcome to my **Time Series Data** repository, where the past meets the future! 📊💥 This collection showcases my experiments with time series data, implementing various forecasting models, and diving deep into techniques that help unlock hidden insights. If you're passionate about predicting the future from past trends, you’re in the right place! 🔮

In this repository, I explore everything from **data preprocessing** to advanced **machine learning models** tailored for time series forecasting. Whether you are tackling stock price prediction, weather forecasting, or demand prediction, this space is designed to help you understand and experiment with **real-world time series problems**. 🚀🌟

---

## 🧠 What’s Inside? 🔍

In this repository, you’ll find a range of **experiments**, **projects**, and **mini-notebooks** focused on time series data:

### 💻 **Time Series Forecasting Models**

- **ARIMA**, **Exponential Smoothing**, **Prophet**: Explore classical forecasting methods and how they fit with time series data.

- **LSTM & GRU Networks**: Dive into deep learning techniques for sequential data and build neural networks that capture time dependencies.

### 📊 **Data Preprocessing & Feature Engineering**

- Handling **missing data**, **outliers**, and **seasonal adjustments**.

- Transforming time series data to make it suitable for machine learning models.

### 🔮 **Exploring Advanced Models**

- Building and experimenting with **AutoARIMA**, **SARIMA**, and **other custom forecasting methods**.

- Implementing **ensemble methods** and hybrid models for better predictions.

### 🌍 **Real-World Applications**

- Apply time series forecasting to real datasets: financial data, weather patterns, and sales prediction.

- Experiment with **model validation techniques** and evaluate performance on multiple datasets.

---

## 🎇 Why This Repository? 🤩

- **Hands-On Learning**: Learn by building and experimenting with real time series models and datasets! 🎉

- **Practical Applications**: Each notebook brings the theory to life with **real-world data** and forecasting challenges. 📊

- **Exploring the Future**: Time series is all about predicting what's coming next—here, we do that with **AI-powered solutions**! 🤖

- **Continuous Updates**: Expect frequent updates as I experiment with new methods, improve models, and explore cutting-edge trends in time series analysis. 🚀

---

## 📅 Regularly Updated & Expanding 🚀

This repository will be **constantly updated** with new experiments, techniques, and improvements in time series forecasting. You’ll always find fresh insights and approaches as I experiment with advanced models and data. 🌱

---

## ✨ Contributions Welcome! 🌟

This space is a place for **learning and collaboration**. Feel free to contribute by:

- Opening **issues** or **pull requests** to suggest improvements or share your own experiments.

- Sharing **ideas** for new forecasting techniques, projects, or models you’d like to see.

- **Forking** the repository, exploring the notebooks, and contributing to the journey!

Let's learn and grow together! 🌱

---

## 🛠 License & Usage 📄

This repository is licensed under the **MIT License** 🎉. You are free to use, modify, and distribute the repository as long as you follow the terms outlined in the license file. 

Make sure to give appropriate credit to the original author, and feel free to explore, experiment, and make it your own! 🌟

---

🎆 **Let's Unlock the Power of Time Series Data Together!** 🎇  

Thanks for exploring my repository! I hope it helps you dive into time series forecasting and bring new insights to your own work. Let’s continue experimenting and pushing the boundaries of data analysis together! 🌐✨