{"id":145937,"date":"2025-07-16T16:31:00","date_gmt":"2025-07-16T11:01:00","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=145937"},"modified":"2025-07-16T16:31:00","modified_gmt":"2025-07-16T11:01:00","slug":"salary-prediction-using-machine-learning","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/","title":{"rendered":"ML Project – Salary Prediction Based-on Skills and Experience using Gradient Boosting"},"content":{"rendered":"

Program 1<\/h3>\n

Salary Prediction Dataset<\/strong><\/a><\/p>\n

# Salary Prediction Based on Skills and Experience using Gradient Boosting\r\nimport pandas as pd\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.preprocessing import OneHotEncoder\r\nfrom sklearn.compose import ColumnTransformer\r\nfrom sklearn.pipeline import Pipeline\r\nfrom sklearn.ensemble import GradientBoostingRegressor\r\nfrom sklearn.metrics import mean_squared_error, r2_score\r\n\r\n# Step 2: Load dataset\r\ndf = pd.read_csv(\"D:\/\/scikit_data\/gbm\/salary_prediction_dataset.csv\")\r\n\r\n# Input(Independed)  output(Depended)\r\nX = df.drop(\"Salary(LPA)\", axis=1) # Indepdend\r\ny = df[\"Salary(LPA)\"] # Depended\r\n\r\n# Step 4: Preprocessing for categorical features\r\ncategorical_cols = [\"EducationLevel\", \"JobRole\"]\r\nnumerical_cols = [\"YearsExperience\", \"SkillPython\", \"SkillSQL\", \"SkillML\"]\r\n\r\npreprocessor = ColumnTransformer([\r\n    (\"cat\", OneHotEncoder(drop=\"first\"), categorical_cols)\r\n], remainder='passthrough')\r\n# OneHotEncoder: Converts these into binary features (0 or 1)\r\n# drop=\"first\" avoids dummy variable trap\r\n# remainder='passthrough': Leaves numerical columns unchanged\r\npreprocessor\r\n\r\nmodel = Pipeline(steps=[\r\n    (\"preprocessing\", preprocessor),\r\n    (\"regressor\", GradientBoostingRegressor(n_estimators=100, learning_rate=0.1, max_depth=3, random_state=42))\r\n])\r\nmodel\r\n# Preprocessing (encoding)\r\n# Gradient Boosting model\r\n# This makes training cleaner and repeatable.\r\n\r\n#Split DataSet\r\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\r\n\r\n# Step 7: Train the model\r\nmodel.fit(X_train, y_train)\r\n\r\n# Step 8: Predictions and Evaluation\r\ny_pred = model.predict(X_test)\r\nrmse = mean_squared_error(y_test, y_pred, squared=False)\r\nr2 = r2_score(y_test, y_pred)\r\n\r\nprint(\" Gradient Boosting Model Performance:\")\r\nprint(f\"RMSE: {rmse:.2f}\")\r\nprint(f\"R\u00b2 Score: {r2:.2f}\")\r\n\r\n# \ud83d\udd39 Step 9: Accept user input and make a salary prediction\r\nprint(\"\\n Enter details to predict your expected salary (LPA):\")\r\n\r\n# Get user input\r\nexperience = float(input(\"Years of Experience: \"))\r\neducation = input(\"Education Level (High School \/ Bachelors \/ Masters \/ PhD): \")\r\njob_role = input(\"Job Role (Data Analyst \/ Data Scientist \/ Software Engineer): \")\r\npython_skill = int(input(\"Do you know Python? (1 for Yes, 0 for No): \"))\r\nsql_skill = int(input(\"Do you know SQL? (1 for Yes, 0 for No): \"))\r\nml_skill = int(input(\"Do you know Machine Learning? (1 for Yes, 0 for No): \"))\r\n\r\n# Create a DataFrame for the input\r\ninput_data = pd.DataFrame([\r\n    {\r\n    \"YearsExperience\": experience,\r\n    \"EducationLevel\": education,\r\n    \"JobRole\": job_role,\r\n    \"SkillPython\": python_skill,\r\n    \"SkillSQL\": sql_skill,\r\n    \"SkillML\": ml_skill\r\n}\r\n])\r\n\r\n# Predict using the trained model\r\npredicted_salary = model.predict(input_data)[0]\r\n\r\nprint(f\"\\n Estimated Salary (LPA): {predicted_salary:.2f}\")\r\n<\/pre>\n
Program 1 Salary Prediction Dataset # Salary Prediction Based on Skills and Experience using Gradient Boosting import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import OneHotEncoder from sklearn.compose import ColumnTransformer from sklearn.pipeline...<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[8431,33127,33128,20697,34920,33136,34918,34919,34917,33134],"class_list":["post-145937","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-machine-learning","tag-machine-learning-practical","tag-machine-learning-program","tag-machine-learning-project","tag-machine-learning-salary-prediction-using-gradient-boosting","tag-salary-prediction","tag-salary-prediction-based-on-skills-and-experience-using-gradient-boosting","tag-salary-prediction-project","tag-salary-prediction-using-gradient-boosting","tag-salary-prediction-using-machine-learning"],"yoast_head":"\nML Project - Salary Prediction Based-on Skills and Experience using Gradient Boosting - DataFlair<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ML Project - Salary Prediction Based-on Skills and Experience using Gradient Boosting - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Program 1 Salary Prediction Dataset # Salary Prediction Based on Skills and Experience using Gradient Boosting import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import OneHotEncoder from sklearn.compose import ColumnTransformer from sklearn.pipeline...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-16T11:01:00+00:00\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"ML Project - Salary Prediction Based-on Skills and Experience using Gradient Boosting - DataFlair","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/","og_locale":"en_US","og_type":"article","og_title":"ML Project - Salary Prediction Based-on Skills and Experience using Gradient Boosting - DataFlair","og_description":"Program 1 Salary Prediction Dataset # Salary Prediction Based on Skills and Experience using Gradient Boosting import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import OneHotEncoder from sklearn.compose import ColumnTransformer from sklearn.pipeline...","og_url":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-07-16T11:01:00+00:00","author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"ML Project – Salary Prediction Based-on Skills and Experience using Gradient Boosting","datePublished":"2025-07-16T11:01:00+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/"},"wordCount":16,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["machine learning","machine learning practical","machine learning program","machine learning project","machine learning salary prediction using gradient boosting","salary prediction","salary prediction based on skills and experience using gradient boosting","salary prediction project","salary prediction using gradient boosting","salary prediction using machine learning"],"articleSection":["Machine Learning Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/","url":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/","name":"ML Project - Salary Prediction Based-on Skills and Experience using Gradient Boosting - DataFlair","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/#website"},"datePublished":"2025-07-16T11:01:00+00:00","breadcrumb":{"@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/data-flair.training\/blogs\/salary-prediction-using-machine-learning\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Blog Home","item":"https:\/\/data-flair.training\/blogs\/"},{"@type":"ListItem","position":2,"name":"Machine Learning Tutorials","item":"https:\/\/data-flair.training\/blogs\/category\/machine-learning\/"},{"@type":"ListItem","position":3,"name":"ML Project – Salary Prediction Based-on Skills and Experience using Gradient Boosting"}]},{"@type":"WebSite","@id":"https:\/\/data-flair.training\/blogs\/#website","url":"https:\/\/data-flair.training\/blogs\/","name":"DataFlair","description":"Learn Today. Lead Tomorrow.","publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/data-flair.training\/blogs\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/data-flair.training\/blogs\/#organization","name":"DataFlair","url":"https:\/\/data-flair.training\/blogs\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/","url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","contentUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","width":106,"height":48,"caption":"DataFlair"},"image":{"@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/DataFlairWS\/","https:\/\/x.com\/DataFlairWS","https:\/\/www.linkedin.com\/company\/dataflair-web-services-pvt-ltd\/","https:\/\/www.youtube.com\/user\/DataFlairWS"]},{"@type":"Person","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445","name":"DataFlair Team","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","caption":"DataFlair Team"},"description":"DataFlair Team provides high-impact content on programming, Java, Python, C++, DSA, AI, ML, data Science, Android, Flutter, MERN, Web Development, and technology. We make complex concepts easy to grasp, helping learners of all levels succeed in their tech careers.","url":"https:\/\/data-flair.training\/blogs\/author\/dfteam6\/"}]}},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145937","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/users\/581"}],"replies":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/comments?post=145937"}],"version-history":[{"count":3,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145937\/revisions"}],"predecessor-version":[{"id":145974,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145937\/revisions\/145974"}],"wp:attachment":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/media?parent=145937"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/categories?post=145937"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/tags?post=145937"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}