Update README.md

README.md

@@ -1,7 +1,7 @@
-# Climate Analysis and Prediction Project
+# Global Temperature Prediction and Analysis
 
 ## Overview
-Investigating temperature changes over time and predicting future temperature patterns regionally and globally stands as the central challenge of this project. To accomplish this, we will employ time series forecasting methods such as neural networks, ARIMA and SARIMAX on the GISTEMP v4 dataset from NASA.
+This project aims to investigate temperature changes over time and predict future temperature patterns on a regional and global scale. We employ time series forecasting methods, including neural networks, ARIMA, and SARIMAX, using the GISTEMP v4 dataset from NASA.
 
 ## Table of Contents
 - [Project Structure](#project-structure)
@@ -14,16 +14,20 @@ Investigating temperature changes over time and predicting future temperature pa
 - [License](#license)
 
 ## Project Structure
-- **global_temp_nn/**: Jupyter notebooks for data exploration, cleaning, analysis, and Neural Network.
-- **arima_sarima/**: Jupyter notebooks for ARIMA and SARIMAX Time Series Forecasting.
+- **global_temp_nn/**: Jupyter notebooks for data exploration, cleaning, analysis, and neural network implementation.
+- **arima_sarima/**: Jupyter notebooks for ARIMA and SARIMAX time series forecasting.
 - **images/**: Contains images generated during the analysis.
 - **data/**: Dataset files used in the project.
 - **README.md**: Project overview and instructions.
-- **'video.avi'**: Temperature Anomalies plotted on world map from 1880 to 2023
+- **temperature_video_june.avi**: Temperature anomalies plotted on a world map from 1880 to 2023.
 
+## Video
+
+![temperature_video_june](https://github.com/shub-garg/Global-Temperature-Prediction-and-Analysis-using-ARIMA-SARIMAX-and-Neural-Network/assets/52582943/ed3d12a1-6545-4df3-84e7-a5ddce9e47c0)
 
 ## Data
 The dataset used in this project includes:
+
 - Global Surface Temperatures
 - Northern Hemisphere Temperatures
 - Southern Hemisphere Temperatures
@@ -32,18 +36,28 @@ The dataset used in this project includes:
 
 ## Analysis and Modeling
 - **Exploratory Data Analysis (EDA)**: Initial exploration of the dataset to understand patterns and trends.
-- *Data Cleaning*: Handling missing values, interpolation, and ensuring data integrity.
-- *Time Series Forecasting*: Utilizing ARIMA and SARIMAX for time series forecasting.
-- *Neural Network Models*: Implementing neural networks for more complex analyses.
+- **Data Cleaning**: Handling missing values, interpolation, and ensuring data integrity.
+- **Time Series Forecasting**: Utilizing ARIMA and SARIMAX for time series forecasting.
+- **Neural Network Models**: Implementing neural networks for more complex analyses.
+
+## Results
+- Visualizations of temperature anomalies over time.
+- Forecasts of future temperature trends using ARIMA and SARIMAX.
+- Neural network predictions for complex analysis of temperature patterns.
 
 ## How to Run
 Download the zip file and run the individual Jupyter notebooks:
-1. global_temp_nn.inpy
-2. arima_sarimax.inpy
+1. `global_temp_nn.ipynb`
+2. `arima_sarimax.ipynb`
 
 ## Dependencies
-Tensorflow 
-Statsmodel
+- TensorFlow
+- Statsmodels
+
+Install the required packages using:
+```bash
+pip install tensorflow statsmodels
+```
 
 ## Contributing
 Shubham Garg- [email protected]