{"id":20733341,"url":"https://github.com/moindalvs/simple_linear_regression_2","last_synced_at":"2026-04-25T09:03:59.808Z","repository":{"id":127429520,"uuid":"471666589","full_name":"MoinDalvs/Simple_Linear_regression_2","owner":"MoinDalvs","description":"Building a prediction model for Salary hike using Years of Experience","archived":false,"fork":false,"pushed_at":"2022-03-21T18:01:01.000Z","size":1439,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-18T00:43:54.309Z","etag":null,"topics":["data-transformation","log-transformation","ols-regression","ordinary-least-squares","prediction-model","scipy-stats","simple-linear-regression","sklearn-library"],"latest_commit_sha":null,"homepage":"","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/MoinDalvs.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,"publiccode":null,"codemeta":null}},"created_at":"2022-03-19T10:49:52.000Z","updated_at":"2023-01-08T11:53:54.000Z","dependencies_parsed_at":null,"dependency_job_id":"b3f4f1cd-e086-4453-b857-f4c372a1b966","html_url":"https://github.com/MoinDalvs/Simple_Linear_regression_2","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FSimple_Linear_regression_2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FSimple_Linear_regression_2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FSimple_Linear_regression_2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FSimple_Linear_regression_2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MoinDalvs","download_url":"https://codeload.github.com/MoinDalvs/Simple_Linear_regression_2/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243016759,"owners_count":20222303,"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":["data-transformation","log-transformation","ols-regression","ordinary-least-squares","prediction-model","scipy-stats","simple-linear-regression","sklearn-library"],"created_at":"2024-11-17T05:24:49.350Z","updated_at":"2026-04-25T09:03:59.723Z","avatar_url":"https://github.com/MoinDalvs.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple_Linear_regression_2\n## Building a prediction model for Salary hike\n### Building a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python.\n\n### Step 1 Importing Data\n### Step 2 Performing EDA On Data\n#### a.) Checking Datatype\n#### b.) Checking for Null Values\n#### c.) Checking for Duplicate Values\n### Step 3 Plotting the data to check for outliers\n### Step 4 Checking the Correlation between variables\n### Step 5 Checking for Homoscedasticity or Hetroscedasticity\n### Step 6 Feature Engineering\n#### a.) Trying different transformation of data to estimate normal distribution and to remove any skewness\n### Step 7 Fitting a Linear Regression Model\n#### a.) Using Ordinary least squares (OLS) regression\n#### b.) Square Root transformation on data\n#### c.) Cube Root transformation on Data\n#### d.) Log transformation on Data\n### Step 8 Residual Analysis\n#### a.) Test for Normality of Residuals (Q-Q Plot)\n#### b.) Residual Plot to check Homoscedasticity or Hetroscedasticity\n### Step 9 Model Validation\n#### a.) Comparing different models with respect to their Root Mean Squared Errors\n### Step 10 Predicting values from Model with Log Transformation on the Data\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoindalvs%2Fsimple_linear_regression_2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmoindalvs%2Fsimple_linear_regression_2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoindalvs%2Fsimple_linear_regression_2/lists"}