{"id":21246723,"url":"https://github.com/soumyadipta2020/ml_forecasting","last_synced_at":"2025-10-02T15:31:23.791Z","repository":{"id":252231065,"uuid":"839444310","full_name":"Soumyadipta2020/ml_forecasting","owner":"Soumyadipta2020","description":"ML Forecasting on EV Population","archived":true,"fork":false,"pushed_at":"2024-12-03T17:49:17.000Z","size":8028,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-15T04:45:16.300Z","etag":null,"topics":["data-science","eda","exploratory-data-analysis","holt-winters-forecasting","jupyter-notebook","machine-learning","modelling","prophet","python","python3","sarima","statistical-analysis","statistical-models","visualization"],"latest_commit_sha":null,"homepage":"https://connect.posit.cloud/Soumyadipta2020/content/019131da-9fc1-ae2b-821a-b865ab76df9c","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Soumyadipta2020.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-08-07T16:09:50.000Z","updated_at":"2025-01-13T17:31:28.000Z","dependencies_parsed_at":"2024-12-03T18:41:15.998Z","dependency_job_id":null,"html_url":"https://github.com/Soumyadipta2020/ml_forecasting","commit_stats":null,"previous_names":["soumyadipta2020/ml_forecasting"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Soumyadipta2020/ml_forecasting","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Soumyadipta2020%2Fml_forecasting","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Soumyadipta2020%2Fml_forecasting/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Soumyadipta2020%2Fml_forecasting/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Soumyadipta2020%2Fml_forecasting/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Soumyadipta2020","download_url":"https://codeload.github.com/Soumyadipta2020/ml_forecasting/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Soumyadipta2020%2Fml_forecasting/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278028939,"owners_count":25918069,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-02T02:00:08.890Z","response_time":67,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","eda","exploratory-data-analysis","holt-winters-forecasting","jupyter-notebook","machine-learning","modelling","prophet","python","python3","sarima","statistical-analysis","statistical-models","visualization"],"created_at":"2024-11-21T02:03:42.835Z","updated_at":"2025-10-02T15:31:22.154Z","avatar_url":"https://github.com/Soumyadipta2020.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# EV Population ↔ ML Forecasting 🚗⚡\n\n![GitHub Repo stars](https://img.shields.io/github/stars/Soumyadipta2020/ml_forecasting?style=social)\n![GitHub forks](https://img.shields.io/github/forks/Soumyadipta2020/ml_forecasting?style=social)\n![GitHub license](https://img.shields.io/github/license/Soumyadipta2020/ml_forecasting)\n[![HitCount](https://hits.dwyl.com/Soumyadipta2020/ml_forecasting.svg?style=flat-square)](http://hits.dwyl.com/Soumyadipta2020/ml_forecasting)\n\nThis repository contains a machine learning forecasting project designed to predict the on-road population of electric vehicles (EVs) for the next 5 years. The project leverages Python and relevant libraries to analyze historical data and generate future projections.\n\n## 📂 **Project Files**\n1. **`forecasting.ipynb`**  \n   Jupyter Notebook containing the complete code for data preprocessing, model training, forecasting, and visualization.\n   \n2. **`Electric_Vehicle_Population_Data.csv`**  \n   Historical dataset used for training and validating the forecasting model. It includes details about the EV population growth over time.\n\n## 🚀 **Features**\n- **Data Analysis:** Insights into historical trends of electric vehicle adoption.\n- **Forecasting Model:** Time series forecasting using machine learning techniques.\n- **Visualization:** Graphical representation of past trends and future projections.\n\n## 🛠️ **Technologies Used**\n- Python (Pandas, NumPy, Prophet)\n- Jupyter Notebook\n- Plotly for visualization\n\n## 📊 **Forecast Objective**\n- Predict the number of electric vehicles on the road for the next 5 years based on historical data.\n- Analyze growth trends to support planning and decision-making for EV infrastructure and policy.\n\n## 📈 **How to Use**\n1. Clone this repository:\n   ```bash\n   git clone https://github.com/Soumyadipta2020/ml_forecasting.git\n   cd ml_forecasting\n   ```\n\n2. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. Open the Jupyter Notebook:\n   ```bash\n   jupyter notebook forecasting.ipynb\n   ```\n\n4. Run each cell to preprocess the data, train the model, and visualize the results.\n\n## 💡 Contribution\n\nContributions are welcome! If you have ideas to enhance the app or fix issues, feel free to fork the repository, make changes, and submit a pull request.\n\nSteps to Contribute:\n\n1. Fork this repository.\n2. Create a new branch: `git checkout -b feature-name`\n3. Commit your changes: `git commit -m \"Add feature-name\"`\n4. Push to your branch: `git push origin feature-name`\n5. Open a Pull Request.\n\n---\n\nHappy Forecasting! 🌍🔌\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumyadipta2020%2Fml_forecasting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsoumyadipta2020%2Fml_forecasting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumyadipta2020%2Fml_forecasting/lists"}