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Author: Archi20876

Data Analysis/Time Series Forecasting on Global Warming/README.md

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+# Time Series Forecasting on Global Warming📈
+
+This project focuses on using time series forecasting techniques to analyze and predict future trends related to global warming. By examining historical data on global temperatures, carbon emissions, and other climate-related variables, the project aims to model future climate patterns and provide insights into the ongoing issue of climate change. Understanding these trends can help policymakers, scientists, and environmentalists take proactive measures to address the challenges of global warming.
+
+### Approach:
+
+- Data Collection: Compile historical climate data from reputable sources, such as NASA, NOAA, and the IPCC, including global temperature records, CO2 concentrations, and oceanic measurements.
+
+- Data Cleaning & Preparation: Process and clean the data to remove anomalies, handle missing values, and standardize variables for accurate analysis.
+
+- Exploratory Data Analysis (EDA):Analyze seasonal variations and anomalies in the data to understand how certain periods or events affect climate trends.
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+- Time Series Forecasting Models:Develop forecasting models with Prophet to predict future global temperatures and other climate-related metrics.
+Compare model performance to select the best approach for accurate long-term forecasts.
+
+- Evaluation & Optimization: Assess model accuracy using metrics like Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and optimize models for better predictions.
+
+
+###  Applications:
+
+- Environmental Organizations: Raise awareness about global warming trends and advocate for sustainable practices.
+- Researchers & Scientists: Gain insights into the future of climate change, enabling further research on its impact and potential solutions.
+- Educational Institutions: Provide data-driven resources for teaching about climate change and its effects on the environment.
+
+  
+
+  To view the Analysis 👉 [Time series forecasting on Global Warming.ipynb](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Time%20Series%20Forecasting%20on%20Global%20Warming/EDA%20-%20Time%20Series%20Forecasting%20on%20Global%20Warming%20Trends.ipynb)
+  
+  To view the Datasets 👉 [long format Annual surface temp](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Time%20Series%20Forecasting%20on%20Global%20Warming/long_format_annual_surface_temp.csv)
+                           [Wide format Annual surface temp](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Time%20Series%20Forecasting%20on%20Global%20Warming/wide_format_annual_surface_temp.csv)
+                           [Max_Min Dataset](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Time%20Series%20Forecasting%20on%20Global%20Warming/Max_Min_Dataset.csv)