{"id":27044243,"url":"https://github.com/igopalakrishna/ann-for-regression","last_synced_at":"2025-07-08T23:07:22.667Z","repository":{"id":222687796,"uuid":"758107036","full_name":"igopalakrishna/ANN-for-Regression","owner":"igopalakrishna","description":null,"archived":false,"fork":false,"pushed_at":"2024-02-15T16:32:48.000Z","size":1975,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T05:31:18.448Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/igopalakrishna.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2024-02-15T16:29:30.000Z","updated_at":"2024-02-15T16:30:08.000Z","dependencies_parsed_at":"2024-02-15T17:54:20.273Z","dependency_job_id":null,"html_url":"https://github.com/igopalakrishna/ANN-for-Regression","commit_stats":null,"previous_names":["igopalakrishna/ann-for-regression"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/igopalakrishna/ANN-for-Regression","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/igopalakrishna%2FANN-for-Regression","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/igopalakrishna%2FANN-for-Regression/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/igopalakrishna%2FANN-for-Regression/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/igopalakrishna%2FANN-for-Regression/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/igopalakrishna","download_url":"https://codeload.github.com/igopalakrishna/ANN-for-Regression/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/igopalakrishna%2FANN-for-Regression/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264363793,"owners_count":23596507,"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","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":[],"created_at":"2025-04-05T05:28:48.695Z","updated_at":"2025-07-08T23:07:22.644Z","avatar_url":"https://github.com/igopalakrishna.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ANN-for-Regression\n\nThe objective is to create a data model that predicts the net hourly electrical energy output (EP) of the plant using available hourly average ambient variables.\n\nThis complex, real-world Deep Learning challenge that covers everything from data preprocessing to building and training an ANN, while utilizing the Machine Learning library, Tensorflow 2.0, and Google Colab, the free, browser-based notebook environment that runs completely in the cloud. \n\nSteps:\n\nPart 1: Data Preprocessing\n\n    Importing the dataset\n\n    Splitting the dataset into the training set and test set\n\nPart 2: Building an ANN\n\n    Initializing the ANN\n\n    Adding the input layer and the first hidden layer\n\n    Adding the output layer\n\n    Compiling the ANN\n\nPart 3: Training the ANN\n\n    Training the ANN model on the training set\n\n    Predicting the results of the test set\n\n\nMore about Combined-Cycle Power Plants\n\nA combined-cycle power plant is an electrical power plant in which a Gas Turbine (GT) and a Steam Turbine (ST) are used in combination to produce more electrical energy from the same fuel than that would be possible from a single cycle power plant.\n\nThe gas turbine compresses air and mixes it with a fuel heated to a very high temperature. The hot air-fuel mixture moves through the blades, making them spin. The fast-spinning gas turbine drives a generator to generate electricity. The exhaust (waste) heat escaped through the exhaust stack of the gas turbine is utilized by a Heat Recovery Steam Generator (HSRG) system to produce steam that spins a steam turbine. This steam turbine drives a generator to produce additional electricity. CCCP is assumed to produce 50% more energy than a single power plant.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figopalakrishna%2Fann-for-regression","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Figopalakrishna%2Fann-for-regression","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figopalakrishna%2Fann-for-regression/lists"}