update to main file

src/file_manage.py

@@ -0,0 +1,33 @@
+import streamlit as st 
+import os
+
+SAVE_DIR = 'uploads'
+os.makedirs(SAVE_DIR, exist_ok=True)
+
+def upload_csv():
+    uploaded_file = st.file_uploader("Choose a CSV file",type="csv")
+    
+    if uploaded_file is not None:
+        # Save the uploaded file to a specific directory
+        save_path = os.path.join('uploads', uploaded_file.name)
+        with open(save_path, 'wb') as f:
+            f.write(uploaded_file.getbuffer())
+        st.success(f"File {uploaded_file.name} uploaded successfully!")
+        
+def list_files():
+    st.subheader("List of Uploaded Files")
+    files = os.listdir('uploads')
+    if files:
+        for file in files:
+            col1, col2 = st.columns([10, 1])
+            col1.write(file)
+            if col2.button("Delete", key=file):
+                os.remove(os.path.join('uploads',file))
+                st.success(f'File {file} deleted successfully!')
+                st.rerun()
+    else:
+        st.info("No files uploaded yet.")
+    
+    return files
+
+   

src/mapping/Advertising.json

@@ -0,0 +1 @@
+{}

src/mapping/Dataset09-Employee-salary-prediction.json

@@ -0,0 +1,187 @@
+{
+    "Gender": {
+        "Female": 0,
+        "Male": 1
+    },
+    "Education Level": {
+        "Bachelor's": 0,
+        "Master's": 1,
+        "PhD": 2
+    },
+    "Job Title": {
+        "Account Manager": 0,
+        "Accountant": 1,
+        "Administrative Assistant": 2,
+        "Business Analyst": 3,
+        "Business Development Manager": 4,
+        "Business Intelligence Analyst": 5,
+        "CEO": 6,
+        "Chief Data Officer": 7,
+        "Chief Technology Officer": 8,
+        "Content Marketing Manager": 9,
+        "Copywriter": 10,
+        "Creative Director": 11,
+        "Customer Service Manager": 12,
+        "Customer Service Rep": 13,
+        "Customer Service Representative": 14,
+        "Customer Success Manager": 15,
+        "Customer Success Rep": 16,
+        "Data Analyst": 17,
+        "Data Entry Clerk": 18,
+        "Data Scientist": 19,
+        "Digital Content Producer": 20,
+        "Digital Marketing Manager": 21,
+        "Director": 22,
+        "Director of Business Development": 23,
+        "Director of Engineering": 24,
+        "Director of Finance": 25,
+        "Director of HR": 26,
+        "Director of Human Capital": 27,
+        "Director of Human Resources": 28,
+        "Director of Marketing": 29,
+        "Director of Operations": 30,
+        "Director of Product Management": 31,
+        "Director of Sales": 32,
+        "Director of Sales and Marketing": 33,
+        "Event Coordinator": 34,
+        "Financial Advisor": 35,
+        "Financial Analyst": 36,
+        "Financial Manager": 37,
+        "Graphic Designer": 38,
+        "HR Generalist": 39,
+        "HR Manager": 40,
+        "Help Desk Analyst": 41,
+        "Human Resources Director": 42,
+        "IT Manager": 43,
+        "IT Support": 44,
+        "IT Support Specialist": 45,
+        "Junior Account Manager": 46,
+        "Junior Accountant": 47,
+        "Junior Advertising Coordinator": 48,
+        "Junior Business Analyst": 49,
+        "Junior Business Development Associate": 50,
+        "Junior Business Operations Analyst": 51,
+        "Junior Copywriter": 52,
+        "Junior Customer Support Specialist": 53,
+        "Junior Data Analyst": 54,
+        "Junior Data Scientist": 55,
+        "Junior Designer": 56,
+        "Junior Developer": 57,
+        "Junior Financial Advisor": 58,
+        "Junior Financial Analyst": 59,
+        "Junior HR Coordinator": 60,
+        "Junior HR Generalist": 61,
+        "Junior Marketing Analyst": 62,
+        "Junior Marketing Coordinator": 63,
+        "Junior Marketing Manager": 64,
+        "Junior Marketing Specialist": 65,
+        "Junior Operations Analyst": 66,
+        "Junior Operations Coordinator": 67,
+        "Junior Operations Manager": 68,
+        "Junior Product Manager": 69,
+        "Junior Project Manager": 70,
+        "Junior Recruiter": 71,
+        "Junior Research Scientist": 72,
+        "Junior Sales Representative": 73,
+        "Junior Social Media Manager": 74,
+        "Junior Social Media Specialist": 75,
+        "Junior Software Developer": 76,
+        "Junior Software Engineer": 77,
+        "Junior UX Designer": 78,
+        "Junior Web Designer": 79,
+        "Junior Web Developer": 80,
+        "Marketing Analyst": 81,
+        "Marketing Coordinator": 82,
+        "Marketing Manager": 83,
+        "Marketing Specialist": 84,
+        "Network Engineer": 85,
+        "Office Manager": 86,
+        "Operations Analyst": 87,
+        "Operations Director": 88,
+        "Operations Manager": 89,
+        "Principal Engineer": 90,
+        "Principal Scientist": 91,
+        "Product Designer": 92,
+        "Product Manager": 93,
+        "Product Marketing Manager": 94,
+        "Project Engineer": 95,
+        "Project Manager": 96,
+        "Public Relations Manager": 97,
+        "Recruiter": 98,
+        "Research Director": 99,
+        "Research Scientist": 100,
+        "Sales Associate": 101,
+        "Sales Director": 102,
+        "Sales Executive": 103,
+        "Sales Manager": 104,
+        "Sales Operations Manager": 105,
+        "Sales Representative": 106,
+        "Senior Account Executive": 107,
+        "Senior Account Manager": 108,
+        "Senior Accountant": 109,
+        "Senior Business Analyst": 110,
+        "Senior Business Development Manager": 111,
+        "Senior Consultant": 112,
+        "Senior Data Analyst": 113,
+        "Senior Data Engineer": 114,
+        "Senior Data Scientist": 115,
+        "Senior Engineer": 116,
+        "Senior Financial Advisor": 117,
+        "Senior Financial Analyst": 118,
+        "Senior Financial Manager": 119,
+        "Senior Graphic Designer": 120,
+        "Senior HR Generalist": 121,
+        "Senior HR Manager": 122,
+        "Senior HR Specialist": 123,
+        "Senior Human Resources Coordinator": 124,
+        "Senior Human Resources Manager": 125,
+        "Senior Human Resources Specialist": 126,
+        "Senior IT Consultant": 127,
+        "Senior IT Project Manager": 128,
+        "Senior IT Support Specialist": 129,
+        "Senior Manager": 130,
+        "Senior Marketing Analyst": 131,
+        "Senior Marketing Coordinator": 132,
+        "Senior Marketing Director": 133,
+        "Senior Marketing Manager": 134,
+        "Senior Marketing Specialist": 135,
+        "Senior Operations Analyst": 136,
+        "Senior Operations Coordinator": 137,
+        "Senior Operations Manager": 138,
+        "Senior Product Designer": 139,
+        "Senior Product Development Manager": 140,
+        "Senior Product Manager": 141,
+        "Senior Product Marketing Manager": 142,
+        "Senior Project Coordinator": 143,
+        "Senior Project Manager": 144,
+        "Senior Quality Assurance Analyst": 145,
+        "Senior Research Scientist": 146,
+        "Senior Researcher": 147,
+        "Senior Sales Manager": 148,
+        "Senior Sales Representative": 149,
+        "Senior Scientist": 150,
+        "Senior Software Architect": 151,
+        "Senior Software Developer": 152,
+        "Senior Software Engineer": 153,
+        "Senior Training Specialist": 154,
+        "Senior UX Designer": 155,
+        "Social Media Manager": 156,
+        "Social Media Specialist": 157,
+        "Software Developer": 158,
+        "Software Engineer": 159,
+        "Software Manager": 160,
+        "Software Project Manager": 161,
+        "Strategy Consultant": 162,
+        "Supply Chain Analyst": 163,
+        "Supply Chain Manager": 164,
+        "Technical Recruiter": 165,
+        "Technical Support Specialist": 166,
+        "Technical Writer": 167,
+        "Training Specialist": 168,
+        "UX Designer": 169,
+        "UX Researcher": 170,
+        "VP of Finance": 171,
+        "VP of Operations": 172,
+        "Web Developer": 173
+    }
+}

src/mapping/cars_train.json

@@ -0,0 +1,41 @@
+{
+    "vhigh": {
+        "high": 0,
+        "low": 1,
+        "med": 2,
+        "vhigh": 3
+    },
+    "high": {
+        "high": 0,
+        "low": 1,
+        "med": 2,
+        "vhigh": 3
+    },
+    "3": {
+        "2": 0,
+        "3": 1,
+        "4": 2,
+        "5more": 3
+    },
+    "more": {
+        "2": 0,
+        "4": 1,
+        "more": 2
+    },
+    "small": {
+        "big": 0,
+        "med": 1,
+        "small": 2
+    },
+    "low": {
+        "high": 0,
+        "low": 1,
+        "med": 2
+    },
+    "unacc": {
+        "acc": 0,
+        "good": 1,
+        "unacc": 2,
+        "vgood": 3
+    }
+}

src/mapping/kidney_disease_dataset.json

@@ -0,0 +1 @@
+{}

src/model_training.py

@@ -0,0 +1,125 @@
+import streamlit as st
+import pandas as pd
+import numpy as np
+import os
+import joblib
+import matplotlib.pyplot as plt
+import sklearn
+import seaborn as sns
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import (
+    accuracy_score, mean_squared_error, r2_score,
+    classification_report, confusion_matrix
+)
+from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
+from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
+from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
+from sklearn.linear_model import LinearRegression
+
+import warnings
+warnings.filterwarnings("ignore")
+
+def model_training():
+    st.title("Model Training & Evaluation")
+
+    # Step 1: Load preprocessed data
+    files = os.listdir('preprocessed_data') if os.path.exists('preprocessed_data') else []
+    if not files:
+        st.warning("No preprocessed data found. Please preprocess a file first.")
+        return
+
+    selected_file = st.selectbox("Select a preprocessed CSV file", files)
+    df = pd.read_csv(os.path.join('preprocessed_data', selected_file))
+    st.write("Data Preview:")
+    st.dataframe(df.head())
+
+    # Step 2: Select target column
+    target_column = st.selectbox("Select Target Column", df.columns)
+    X = df.drop(columns=[target_column])
+    y = df[target_column]
+
+    # Step 3: Detect problem type
+    if y.nunique() <= 20 and y.dtype in ['int64', 'int32']:
+        problem_type = "classification"
+        st.info("Detected as Classification Problem")
+    else:
+        problem_type = "regression"
+        st.info("Detected as Regression Problem")
+
+    # Step 4: Train/Test Split
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+    # Step 5: Define models
+    if problem_type == "classification":
+        models = {
+            "Random Forest Classifier": RandomForestClassifier(),
+            "Decision Tree Classifier": DecisionTreeClassifier(),
+            "KNN Classifier": KNeighborsClassifier()
+        }
+    else:
+        models = {
+            "Random Forest Regressor": RandomForestRegressor(),
+            "Decision Tree Regressor": DecisionTreeRegressor(),
+            "KNN Regressor": KNeighborsRegressor(),
+            "Linear Regression": LinearRegression()
+        }
+
+    # Step 6: Train, Evaluate, and Display Metrics
+    results = []
+    for name, model in models.items():
+        model.fit(X_train, y_train)
+        y_pred = model.predict(X_test)
+
+        if problem_type == "classification":
+            score = (accuracy_score(y_test, y_pred))*100
+        else:
+            score = (r2_score(y_test, y_pred))*100
+
+        results.append((name, score, model, y_pred))
+
+    # Step 7: Show model performance table
+    results_df = pd.DataFrame(results, columns=["Model", "Score", "Trained_Model", "Predictions"])
+    st.write("Model Performance:")
+    st.dataframe(results_df[["Model", "Score"]])
+
+    # Step 8: Best Model Selection
+    best_model_row = results_df.loc[results_df["Score"].idxmax()]
+    st.success(f"Best Model: {best_model_row['Model']} with Score: {best_model_row['Score']:.4f}")
+    #SHOW NAME OF BEST MODEL
+    st.write("Best Model Details:", best_model_row)
+    best_model = best_model_row["Trained_Model"]
+    
+    
+    # Step 9: Detailed Metrics for Best Model
+    st.subheader("Detailed Metrics for Best Model")
+    best_y_pred = best_model_row["Predictions"]
+
+    if problem_type == "classification":
+        st.write("**Accuracy Score:**", accuracy_score(y_test, best_y_pred))
+        st.text("**Classification Report:**")
+        st.text(classification_report(y_test, best_y_pred))
+
+        # Confusion Matrix
+        cm = confusion_matrix(y_test, best_y_pred)
+        fig, ax = plt.subplots()
+        sns.heatmap(cm, annot=True, fmt="d", cmap="Blues", ax=ax)
+        ax.set_xlabel("Predicted")
+        ax.set_ylabel("Actual")
+        st.pyplot(fig)
+
+    else:
+        st.write("**Mean Squared Error:**", np.sqrt(mean_squared_error(y_test, best_y_pred))*100, "%")
+        st.write("**R² Score:**", r2_score(y_test, best_y_pred))
+
+    # Step 10: Save & Download Best Model
+    if st.button("Save Best Model"):
+        st.write("Saving the best model...")
+        st.write(f"Model Name: {best_model_row['Model']}")
+        os.makedirs("saved_models", exist_ok=True)
+        model_path = f"saved_models/{best_model_row['Model'].replace(' ', '_')}.pkl"
+        joblib.dump(best_model_row["Trained_Model"], model_path)
+        st.download_button(
+            label="Download Model",
+            data=open(model_path, "rb").read(),
+            file_name=os.path.basename(model_path)
+        )

src/preprocessed_data/Advertising.csv

@@ -0,0 +1,201 @@
+Unnamed: 0,TV,Radio,Newspaper,Sales
+1,230.1,37.8,69.2,22.1
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src/preprocessed_data/Dataset09-Employee-salary-prediction.csv

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src/preprocessed_data/kidney_disease_dataset.csv

@@ -0,0 +1,2305 @@
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src/preprocessing.py

@@ -0,0 +1,81 @@
+import streamlit as st
+import pandas as pd
+from file_manage import list_files
+import os
+from sklearn.preprocessing import LabelEncoder
+import warnings
+import json
+
+warnings.filterwarnings("ignore")
+
+def preprocess_data():
+    st.title('Data Preprocessing')
+
+    csv_files = list_files()
+
+    if not csv_files:
+        st.warning("No CSV files available for preprocessing.")
+    else:
+        selected_file = st.selectbox('Select a CSV file for Preprocessing', csv_files)
+        if selected_file:
+            df = pd.read_csv(os.path.join('uploads', selected_file))
+            st.write('**Data Preview:**')
+            st.dataframe(df.head())
+
+            # Step 1: Show unique values before encoding
+            if st.button('Show Unique Values'):
+                st.subheader("Unique Values in Each Column")
+                for col in df.columns:
+                    st.write(f"**{col}** ({df[col].dtype}) → {df[col].nunique()} unique values")
+                    st.write(df[col].unique())
+
+            # Step 2: Analyze data
+            if st.button('Analyze Data'):
+                null_counts = df.isnull().sum()
+                null_info = pd.DataFrame({'Column': null_counts.index, 'Null Values': null_counts.values})
+                st.subheader("Null Values Information")
+                st.dataframe(null_info)
+
+                categorical_data = df.select_dtypes(include=['object']).columns.tolist()
+                st.subheader("Categorical Columns")
+                st.write(categorical_data if categorical_data else "No categorical columns found.")
+
+            # Step 3: Preprocess
+            if st.button('Preprocess Data'):
+                labelencoder_mappings = {}  # save the encoded mappings
+
+                for col in df.columns:
+                    # Fill missing values
+                    if df[col].isnull().sum() > 0:
+                        df[col].fillna(df[col].mode()[0], inplace=True)
+
+                    # Encode categorical columns
+                    if df[col].dtype == 'object':
+                        le = LabelEncoder()
+                        df[col] = le.fit_transform(df[col])
+                        mapping_dict = {str(k): int(v) for k, v in zip(le.classes_, le.transform(le.classes_))}
+                        labelencoder_mappings[col] = mapping_dict
+
+                        # Show encoding mapping in Streamlit
+                        st.write(f"**Encoding for column `{col}`:**")
+                        st.json(mapping_dict)
+
+                # Save preprocessed CSV
+                preprocessed_folder = 'preprocessed_data'
+                os.makedirs(preprocessed_folder, exist_ok=True)
+                preprocessed_filename = selected_file
+                df.to_csv(os.path.join(preprocessed_folder, preprocessed_filename), index=False)
+                st.success(f"Preprocessed file saved as {preprocessed_filename}")
+
+                # Save label encoder mappings
+                mapping_folder = "mapping"
+                os.makedirs(mapping_folder, exist_ok=True)
+                mapping_file = os.path.join(mapping_folder, f"{selected_file.split('.')[0]}.json")
+                with open(mapping_file, "w") as f:
+                    json.dump(labelencoder_mappings, f, indent=4)
+                st.success(f"Label encoding mappings saved in {mapping_file}")
+
+                # Show final preprocessed data
+                st.subheader("Preprocessed Data")
+                st.dataframe(df)
+                st.success("Data preprocessing completed successfully!")

src/saved_models/Linear_Regression.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:52ebf4a17fdf32afdea5018871f3cd950c467bacfadf25079ca08f0b21a8534e
+size 905

src/saved_models/Random_Forest_Classifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bf947dc4b88eecfa698852107132f517a625121d202bb3e17428b2acb1b65380
+size 3167337

src/saved_models/Random_Forest_Regressor.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:24b686389d3004e0beb9d53bb4b13c51a9a1fa2c804c10e6f12a591a3e7916b1
+size 1721089

src/streamlit_app.py

@@ -1,40 +1,34 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+from file_manage import upload_csv, list_files
+
+from preprocessing import preprocess_data
+
+from model_training import model_training
+
+
+
+
+
+
+st.set_page_config(page_title='Automation',
+                   page_icon='ai_logo.png', 
+                   layout='wide'
+                   )
+
+st.sidebar.image('ai_logo.png')
+page = st.sidebar.selectbox('Select an Option', ['File Management', 'Preprocessing Data', 'Model Training'])
+
+if page == 'File Management':
+    st.title('File Management')
+    upload_csv()
+    list_files()
+
+elif page == 'Preprocessing Data':
+    st.title('Preprocessing Data')
+    preprocess_data()
+
+
+elif page == 'Model Training':
+    st.title('Model Training')
+    model_training()

src/uploads/Dataset09-Employee-salary-prediction.csv

@@ -0,0 +1,376 @@
+Age,Gender,Education Level,Job Title,Years of Experience,Salary
+32,Male,Bachelor's,Software Engineer,5,90000
+28,Female,Master's,Data Analyst,3,65000
+45,Male,PhD,Senior Manager,15,150000
+36,Female,Bachelor's,Sales Associate,7,60000
+52,Male,Master's,Director,20,200000
+29,Male,Bachelor's,Marketing Analyst,2,55000
+42,Female,Master's,Product Manager,12,120000
+31,Male,Bachelor's,Sales Manager,4,80000
+26,Female,Bachelor's,Marketing Coordinator,1,45000
+38,Male,PhD,Senior Scientist,10,110000
+29,Male,Master's,Software Developer,3,75000
+48,Female,Bachelor's,HR Manager,18,140000
+35,Male,Bachelor's,Financial Analyst,6,65000
+40,Female,Master's,Project Manager,14,130000
+27,Male,Bachelor's,Customer Service Rep,2,40000
+44,Male,Bachelor's,Operations Manager,16,125000
+33,Female,Master's,Marketing Manager,7,90000
+39,Male,PhD,Senior Engineer,12,115000
+25,Female,Bachelor's,Data Entry Clerk,0,35000
+51,Male,Bachelor's,Sales Director,22,180000
+34,Female,Master's,Business Analyst,5,80000
+47,Male,Master's,VP of Operations,19,190000
+30,Male,Bachelor's,IT Support,2,50000
+36,Female,Bachelor's,Recruiter,9,60000
+41,Male,Master's,Financial Manager,13,140000
+28,Female,Bachelor's,Social Media Specialist,3,45000
+37,Female,Master's,Software Manager,11,110000
+24,Male,Bachelor's,Junior Developer,1,40000
+43,Female,PhD,Senior Consultant,15,140000
+33,Male,Master's,Product Designer,6,90000
+50,Male,Bachelor's,CEO,25,250000
+31,Female,Bachelor's,Accountant,4,55000
+29,Male,Master's,Data Scientist,3,75000
+39,Female,Bachelor's,Marketing Specialist,10,65000
+46,Male,PhD,Senior Manager,20,170000
+27,Male,Bachelor's,Technical Writer,2,45000
+35,Female,Bachelor's,HR Generalist,7,60000
+42,Male,Master's,Project Engineer,14,115000
+26,Female,Bachelor's,Customer Success Rep,1,40000
+49,Male,Bachelor's,Sales Executive,21,160000
+34,Female,Master's,UX Designer,5,80000
+48,Male,Master's,Operations Director,18,190000
+30,Male,Bachelor's,Network Engineer,3,60000
+36,Female,Bachelor's,Administrative Assistant,8,45000
+41,Male,Master's,Strategy Consultant,13,130000
+28,Female,Bachelor's,Copywriter,2,40000
+32,Male,Bachelor's,Account Manager,5,75000
+45,Female,Master's,Director of Marketing,16,180000
+38,Male,PhD,Senior Scientist,11,120000
+25,Male,Bachelor's,Help Desk Analyst,0,35000
+51,Female,Bachelor's,Customer Service Manager,22,130000
+33,Male,Master's,Business Intelligence Analyst,7,85000
+40,Female,Bachelor's,Event Coordinator,12,60000
+47,Male,Master's,VP of Finance,19,200000
+29,Female,Bachelor's,Graphic Designer,3,50000
+36,Male,Bachelor's,Sales Manager,9,95000
+27,Female,Master's,UX Researcher,2,65000
+43,Male,PhD,Senior Engineer,17,140000
+30,Female,Bachelor's,Social Media Manager,4,55000
+35,Male,Master's,Product Manager,7,105000
+51,Female,Master's,Director of Operations,23,170000
+29,Male,Bachelor's,Marketing Analyst,3,50000
+40,Female,Bachelor's,HR Manager,12,80000
+47,Male,PhD,Senior Data Scientist,21,180000
+26,Male,Bachelor's,Junior Accountant,1,35000
+38,Female,Master's,Digital Marketing Manager,10,90000
+46,Male,Bachelor's,IT Manager,19,120000
+31,Female,Bachelor's,Customer Service Representative,5,45000
+34,Male,Master's,Business Development Manager,8,90000
+49,Female,Master's,Senior Financial Analyst,18,150000
+33,Male,Bachelor's,Web Developer,6,65000
+39,Female,Bachelor's,Recruiter,11,70000
+45,Male,PhD,Research Director,16,190000
+28,Male,Bachelor's,Technical Support Specialist,2,40000
+42,Female,Master's,Creative Director,14,120000
+37,Male,Bachelor's,Project Manager,10,95000
+50,Female,Bachelor's,Operations Manager,22,160000
+32,Male,Master's,Senior Software Engineer,6,100000
+48,Female,Master's,Human Resources Director,20,180000
+30,Female,Bachelor's,Content Marketing Manager,3,55000
+36,Male,Bachelor's,Technical Recruiter,8,70000
+41,Female,Master's,Data Analyst,13,80000
+25,Male,Bachelor's,Sales Representative,0,30000
+52,Male,PhD,Chief Technology Officer,24,250000
+29,Female,Bachelor's,Junior Designer,2,40000
+34,Female,Master's,Financial Advisor,10,95000
+27,Male,Bachelor's,Junior Account Manager,2,45000
+40,Female,Bachelor's,HR Generalist,15,80000
+46,Male,Master's,Senior Project Manager,21,135000
+31,Female,Bachelor's,Marketing Coordinator,6,55000
+36,Male,PhD,Principal Scientist,11,120000
+29,Female,Bachelor's,Sales Associate,3,40000
+43,Male,Bachelor's,Supply Chain Manager,18,105000
+52,Female,Master's,Senior Marketing Manager,25,170000
+33,Male,Bachelor's,Business Analyst,7,75000
+39,Female,Bachelor's,Training Specialist,12,65000
+47,Male,PhD,Research Scientist,22,160000
+26,Male,Bachelor's,Junior Software Developer,1,35000
+38,Female,Master's,Public Relations Manager,10,90000
+45,Male,Bachelor's,Operations Analyst,20,110000
+31,Female,Bachelor's,Event Coordinator,5,45000
+35,Male,Master's,Product Marketing Manager,8,95000
+49,Female,Master's,Senior HR Manager,19,150000
+33,Male,Bachelor's,Junior Web Developer,5,50000
+39,Female,Master's,Senior Project Coordinator,13,80000
+44,Male,PhD,Chief Data Officer,16,220000
+30,Female,Bachelor's,Digital Content Producer,3,50000
+36,Male,Bachelor's,IT Support Specialist,7,60000
+41,Female,Master's,Senior Marketing Analyst,14,100000
+28,Male,Bachelor's,Customer Success Manager,2,40000
+42,Female,Master's,Senior Graphic Designer,15,110000
+37,Male,Bachelor's,Software Project Manager,9,95000
+50,Female,Bachelor's,Supply Chain Analyst,22,130000
+32,Male,Master's,Senior Business Analyst,6,90000
+23,Female,Bachelor's,Junior Marketing Analyst,0.5,35000
+31,Male,Master's,Senior Financial Analyst,6,95000
+40,Female,Bachelor's,Office Manager,15,65000
+48,Male,PhD,Principal Engineer,20,170000
+29,Female,Bachelor's,Junior HR Generalist,3,45000
+35,Male,Master's,Senior Product Manager,10,120000
+42,Female,Bachelor's,Sales Manager,17,100000
+53,Male,Master's,Director of Marketing,25,180000
+33,Female,Bachelor's,Junior Operations Analyst,5,50000
+38,Male,Bachelor's,Customer Service Manager,11,80000
+44,Female,PhD,Senior Scientist,16,140000
+26,Male,Bachelor's,Junior Accountant,2,40000
+37,Female,Master's,Senior HR Generalist,9,95000
+45,Male,Bachelor's,Sales Operations Manager,18,110000
+32,Female,Bachelor's,Marketing Coordinator,4,50000
+34,Male,Master's,Senior Software Developer,8,105000
+50,Female,Master's,Director of Operations,21,160000
+29,Male,Bachelor's,Junior Web Designer,3,45000
+40,Female,Master's,Senior Training Specialist,12,100000
+47,Male,PhD,Senior Research Scientist,22,160000
+27,Male,Bachelor's,Junior Sales Representative,1,35000
+39,Female,Bachelor's,Administrative Assistant,10,55000
+46,Male,Master's,Senior Project Manager,19,140000
+30,Female,Bachelor's,Junior Marketing Manager,4,50000
+36,Male,Bachelor's,Junior Data Analyst,7,60000
+43,Female,Master's,Senior Product Marketing Manager,14,120000
+28,Male,Bachelor's,Junior Business Analyst,2,40000
+41,Female,Master's,Senior Marketing Manager,13,110000
+33,Male,Bachelor's,Junior Software Developer,5,50000
+47,Male,Bachelor's,Senior Sales Manager,20,135000
+25,Female,Master's,Junior Marketing Specialist,1.5,40000
+34,Male,Bachelor's,Senior Business Analyst,8,90000
+42,Female,PhD,Senior Data Scientist,16,150000
+31,Male,Bachelor's,Junior Project Manager,4,60000
+38,Female,Bachelor's,Senior Accountant,10,80000
+45,Male,Master's,Director of Sales,19,175000
+29,Female,Bachelor's,Junior Recruiter,3,45000
+36,Male,Master's,Senior Business Development Manager,11,120000
+43,Female,PhD,Senior Product Designer,18,140000
+26,Male,Bachelor's,Junior Customer Support Specialist,2,35000
+37,Female,Master's,Senior Marketing Analyst,9,95000
+44,Male,Bachelor's,Senior IT Support Specialist,14,110000
+32,Female,Bachelor's,Junior Financial Analyst,5,50000
+33,Male,Master's,Senior Operations Manager,7,115000
+51,Female,PhD,Director of Human Resources,23,185000
+28,Male,Bachelor's,Junior Software Engineer,2,40000
+39,Female,Bachelor's,Senior Sales Representative,12,90000
+48,Male,Master's,Director of Product Management,21,175000
+30,Female,Bachelor's,Junior Copywriter,3,45000
+35,Male,Bachelor's,Senior Marketing Coordinator,7,80000
+41,Female,Master's,Senior Human Resources Manager,13,120000
+27,Male,Bachelor's,Junior Business Development Associate,1.5,35000
+40,Female,Bachelor's,Senior Account Manager,14,110000
+46,Male,PhD,Senior Researcher,18,150000
+31,Female,Bachelor's,Junior HR Coordinator,4,50000
+34,Male,Master's,Senior Software Engineer,9,105000
+50,Female,Master's,Director of Finance,20,180000
+29,Male,Bachelor's,Junior Marketing Coordinator,2,40000
+,,,,,
+43,Male,Bachelor's,Senior Project Manager,16,140000
+26,Female,Master's,Junior Data Scientist,1.5,45000
+35,Male,Bachelor's,Senior Operations Analyst,7,85000
+42,Female,PhD,Senior Marketing Manager,18,140000
+31,Male,Bachelor's,Junior Accountant,4,50000
+38,Female,Bachelor's,Senior Human Resources Coordinator,10,80000
+46,Male,Master's,Director of Operations,20,170000
+29,Female,Bachelor's,Junior Sales Representative,2,40000
+37,Male,Master's,Senior Business Analyst,9,105000
+44,Female,PhD,Senior UX Designer,15,145000
+27,Male,Bachelor's,Junior Product Manager,2,40000
+36,Female,Bachelor's,Senior Marketing Specialist,8,85000
+43,Male,Bachelor's,Senior IT Project Manager,14,130000
+33,Female,Master's,Senior Financial Analyst,6,95000
+34,Male,Bachelor's,Senior Quality Assurance Analyst,9,100000
+50,Female,PhD,Director of Sales and Marketing,22,180000
+28,Male,Bachelor's,Junior Operations Analyst,1.5,35000
+39,Female,Bachelor's,Senior Account Executive,12,95000
+47,Male,Master's,Director of Business Development,19,170000
+30,Female,Bachelor's,Junior Social Media Manager,3,45000
+34,Male,Bachelor's,Senior Product Manager,7,95000
+40,Female,Master's,Senior Human Resources Specialist,13,120000
+28,Male,Bachelor's,Junior Business Analyst,2,40000
+41,Female,Bachelor's,Senior Marketing Coordinator,11,90000
+45,Male,PhD,Senior Data Analyst,17,155000
+32,Female,Bachelor's,Junior Account Manager,5,55000
+35,Male,Master's,Senior Software Developer,9,110000
+49,Female,Master's,Director of Human Capital,21,180000
+30,Male,Bachelor's,Junior Advertising Coordinator,3,45000
+44,Male,Bachelor's,Senior Sales Manager,16,130000
+27,Female,Master's,Junior UX Designer,1.5,45000
+36,Male,Bachelor's,Senior Accountant,7,90000
+41,Female,PhD,Senior Marketing Director,17,160000
+31,Male,Bachelor's,Junior HR Generalist,4,50000
+39,Female,Bachelor's,Senior Operations Manager,10,120000
+47,Male,Master's,Director of Finance,20,170000
+30,Female,Bachelor's,Junior Marketing Coordinator,2,40000
+38,Male,Master's,Senior IT Consultant,9,110000
+45,Female,PhD,Senior Product Designer,15,150000
+28,Male,Bachelor's,Junior Business Development Associate,2,40000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+44,Male,Bachelor's,Senior Software Engineer,14,130000
+34,Female,Master's,Senior Financial Advisor,6,100000
+35,Male,Bachelor's,Senior Project Coordinator,9,95000
+50,Female,PhD,Director of Operations,22,180000
+29,Male,Bachelor's,Junior Business Operations Analyst,1.5,35000
+40,Female,Bachelor's,Senior Sales Representative,12,100000
+48,Male,Master's,Director of Marketing,19,170000
+31,Female,Bachelor's,Junior Social Media Specialist,3,45000
+33,Male,Bachelor's,Senior Product Development Manager,7,100000
+42,Female,Master's,Senior Human Resources Manager,13,140000
+28,Male,Bachelor's,Junior Financial Analyst,2,40000
+40,Female,Bachelor's,Senior Marketing Manager,11,105000
+46,Male,PhD,Senior Data Scientist,18,160000
+33,Female,Bachelor's,Junior Operations Manager,5,70000
+37,Male,Master's,Senior Software Architect,9,120000
+51,Female,Master's,Director of Human Resources,21,190000
+30,Male,Bachelor's,Junior Marketing Specialist,3,45000
+43,Male,Bachelor's,Senior Project Manager,15,120000
+27,Female,Master's,Junior Research Scientist,1.5,50000
+35,Male,Bachelor's,Senior Operations Analyst,8,85000
+42,Female,PhD,Senior Marketing Manager,13,140000
+32,Male,Bachelor's,Junior Sales Representative,3,45000
+37,Female,Bachelor's,Senior Financial Analyst,9,100000
+45,Male,Master's,Senior Software Developer,16,140000
+33,Female,Bachelor's,Junior Operations Analyst,5,70000
+39,Male,Bachelor's,Senior Marketing Specialist,10,120000
+44,Female,PhD,Senior HR Manager,18,160000
+29,Male,Bachelor's,Junior Business Analyst,1.5,40000
+38,Female,Bachelor's,Senior Product Manager,10,120000
+46,Male,PhD,Senior Data Analyst,19,150000
+34,Female,Bachelor's,Junior Marketing Analyst,6,70000
+36,Male,Bachelor's,Senior Operations Manager,8,95000
+49,Female,Master's,Director of Marketing,21,180000
+31,Male,Bachelor's,Junior Financial Analyst,3,50000
+41,Female,Bachelor's,Senior Project Coordinator,11,95000
+47,Male,Master's,Director of Operations,20,170000
+30,Female,Bachelor's,Junior Marketing Coordinator,2,40000
+38,Male,Master's,Senior IT Consultant,9,110000
+45,Female,PhD,Senior Product Designer,15,150000
+28,Male,Bachelor's,Junior Business Development Associate,2,40000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+44,Male,Bachelor's,Senior Software Engineer,14,130000
+34,Female,Master's,Senior Financial Advisor,6,100000
+35,Male,Bachelor's,Senior Project Coordinator,9,95000
+50,Female,PhD,Director of Operations,22,180000
+29,Male,Bachelor's,Junior Business Operations Analyst,1.5,350
+,,,,,
+37,Female,Bachelor's,Senior Financial Manager,10,120000
+46,Male,PhD,Senior Data Scientist,18,160000
+31,Female,Bachelor's,Junior Marketing Coordinator,3,50000
+42,Male,Bachelor's,Senior Operations Manager,12,110000
+29,Female,Bachelor's,Junior Sales Representative,1.5,40000
+36,Male,Bachelor's,Senior Marketing Specialist,8,95000
+44,Female,Master's,Senior HR Specialist,15,140000
+33,Male,Bachelor's,Junior Operations Manager,4,60000
+39,Female,Bachelor's,Senior Marketing Coordinator,9,110000
+45,Male,PhD,Senior Data Engineer,16,150000
+32,Female,Bachelor's,Junior Marketing Manager,4,60000
+37,Male,Bachelor's,Senior Financial Analyst,8,90000
+47,Female,Master's,Director of Marketing,20,180000
+30,Male,Bachelor's,Junior Business Analyst,2,40000
+38,Female,Bachelor's,Senior Project Manager,9,120000
+46,Male,PhD,Senior Data Analyst,17,160000
+34,Female,Bachelor's,Junior Financial Analyst,5,70000
+36,Male,Bachelor's,Senior Product Manager,8,95000
+49,Female,Master's,Director of Operations,21,180000
+31,Male,Bachelor's,Junior Operations Analyst,3,50000
+41,Female,Bachelor's,Senior Project Coordinator,11,95000
+47,Male,Master's,Director of Marketing,19,170000
+29,Female,Bachelor's,Junior Business Development Associate,1.5,35000
+35,Male,Bachelor's,Senior Financial Manager,9,100000
+44,Female,PhD,Senior Product Designer,15,150000
+33,Male,Bachelor's,Junior Business Analyst,4,60000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+44,Male,Bachelor's,Senior Software Engineer,13,130000
+32,Male,Bachelor's,Junior Product Manager,4,65000
+38,Female,Bachelor's,Senior Business Analyst,10,110000
+49,Male,PhD,Director of Operations,21,180000
+29,Female,Bachelor's,Junior Marketing Specialist,2,40000
+35,Male,Bachelor's,Senior Business Development Manager,7,90000
+45,Female,Master's,Senior HR Manager,14,140000
+33,Male,Bachelor's,Junior Financial Analyst,4,60000
+40,Female,Bachelor's,Senior Marketing Manager,12,130000
+44,Male,PhD,Senior Data Scientist,16,160000
+30,Female,Bachelor's,Junior Operations Coordinator,2,40000
+37,Male,Bachelor's,Senior Marketing Analyst,9,100000
+48,Female,Master's,Director of HR,20,180000
+31,Male,Bachelor's,Junior Project Manager,3,55000
+38,Female,Bachelor's,Senior Operations Coordinator,9,120000
+45,Male,PhD,Senior Data Engineer,16,150000
+33,Female,Bachelor's,Junior Marketing Manager,5,70000
+36,Male,Bachelor's,Senior Business Analyst,8,95000
+49,Female,Master's,Director of Marketing,21,180000
+31,Male,Bachelor's,Junior Operations Analyst,3,50000
+42,Female,Bachelor's,Senior Project Manager,12,120000
+47,Male,Master's,Director of Marketing,19,170000
+29,Female,Bachelor's,Junior Business Development Associate,1.5,35000
+35,Male,Bachelor's,Senior Financial Manager,9,100000
+44,Female,PhD,Senior Product Designer,15,150000
+33,Male,Bachelor's,Junior Business Analyst,4,60000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+44,Male,Bachelor's,Senior Software Engineer,13,130000
+34,Female,Master's,Senior Financial Advisor,6,80000
+36,Male,Bachelor's,Senior Marketing Specialist,8,95000
+30,Female,Bachelor's,Junior HR Coordinator,2,40000
+37,Male,Bachelor's,Senior Business Development Manager,10,120000
+45,Female,Master's,Senior Marketing Manager,16,160000
+32,Male,Bachelor's,Junior Financial Advisor,4,65000
+39,Female,Bachelor's,Senior Project Manager,12,130000
+47,Male,PhD,Director of Engineering,20,180000
+29,Female,Bachelor's,Junior Marketing Analyst,2,40000
+36,Male,Bachelor's,Senior Operations Manager,9,100000
+43,Female,PhD,Senior Data Scientist,15,150000
+32,Male,Bachelor's,Junior Marketing Coordinator,3,55000
+38,Female,Bachelor's,Senior Business Analyst,10,110000
+48,Male,Master's,Director of Marketing,21,180000
+31,Female,Bachelor's,Junior Business Development Associate,3,50000
+40,Male,Bachelor's,Senior Financial Analyst,12,130000
+45,Female,PhD,Senior UX Designer,16,160000
+33,Male,Bachelor's,Junior Product Manager,4,60000
+36,Female,Bachelor's,Senior Marketing Manager,8,95000
+47,Male,Master's,Director of Operations,19,170000
+29,Female,Bachelor's,Junior Project Manager,2,40000
+34,Male,Bachelor's,Senior Operations Coordinator,7,90000
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+33,Male,Bachelor's,Junior Marketing Specialist,5,70000
+35,Female,Bachelor's,Senior Financial Manager,8,90000
+43,Male,Master's,Director of Marketing,18,170000
+31,Female,Bachelor's,Junior Financial Analyst,3,50000
+41,Male,Bachelor's,Senior Product Manager,14,150000
+44,Female,PhD,Senior Data Engineer,16,160000
+33,Male,Bachelor's,Junior Business Analyst,4,60000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+45,Male,Master's,Director of Engineering,19,180000
+28,Female,Bachelor's,Junior Operations Manager,1,35000
+36,Male,Bachelor's,Senior Business Development Manager,8,110000
+44,Female,PhD,Senior Data Scientist,16,160000
+31,Male,Bachelor's,Junior Marketing Coordinator,3,55000
+38,Female,Bachelor's,Senior Business Analyst,10,110000
+48,Male,Master's,Director of Marketing,21,180000
+31,Female,Bachelor's,Junior Business Development Associate,3,50000
+40,Male,Bachelor's,Senior Financial Analyst,12,130000
+45,Female,PhD,Senior UX Designer,16,160000
+33,Male,Bachelor's,Junior Product Manager,4,60000
+36,Female,Bachelor's,Senior Marketing Manager,8,95000
+47,Male,Master's,Director of Operations,19,170000
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+44,Female,PhD,Senior Business Analyst,15,150000
+33,Male,Bachelor's,Junior Marketing Specialist,5,70000
+35,Female,Bachelor's,Senior Financial Manager,8,90000
+43,Male,Master's,Director of Marketing,18,170000
+31,Female,Bachelor's,Junior Financial Analyst,3,50000
+41,Male,Bachelor's,Senior Product Manager,14,150000
+44,Female,PhD,Senior Data Engineer,16,160000
+33,Male,Bachelor's,Junior Business Analyst,4,60000
+35,Female,Bachelor's,Senior Marketing Analyst,8,85000
+43,Male,Master's,Director of Operations,19,170000
+29,Female,Bachelor's,Junior Project Manager,2,40000
+34,Male,Bachelor's,Senior Operations Coordinator,7,90000
+44,Female,PhD,Senior Business Analyst,15,150000

src/uploads/cars_train.csv

@@ -0,0 +1,1382 @@
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src/uploads/kidney_disease_dataset.csv

@@ -0,0 +1,2305 @@
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