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Tweet.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:099b4b93265c576c3f5e07746fae41c2951828e911575dc83e0a480c6d0eb739
+size 63270657

app.py

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+import pandas as pd
+import streamlit as st
+import joblib
+
+from sklearn.preprocessing import StandardScaler, OneHotEncoder
+from sklearn.model_selection import train_test_split
+from sklearn.compose import ColumnTransformer
+
+# Veriyi yükleme ve sütun isimlerini güncelleme
+df = pd.read_csv('train.csv')
+
+# Bağımlı ve bağımsız değişkenlerin seçimi
+x = df.drop(['essay_id', 'text'], axis=1)
+y = df[['text']]
+
+# Eğitim ve test verilerini ayırma
+x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)
+
+# Ön işleme (StandardScaler ve OneHotEncoder)
+preprocessor = ColumnTransformer(
+    transformers=[
+        ('num', StandardScaler(), ['feeling']),
+        ('cat', OneHotEncoder(), ['text'])
+    ]
+)
+
+# Streamlit uygulaması
+def rings_pred(feeling, text):
+    input_data = pd.DataFrame({
+        'text': [text],
+        'feeling': [feeling]
+        
+    })
+    
+    
+    input_data_transformed = preprocessor.fit_transform(input_data)
+
+    model = joblib.load('Tweet.pkl')
+
+    prediction = model.predict(input_data_transformed)
+    return float(prediction[0])
+
+st.title("Abalone Veri seti ile Yaş Tahmini Regresyon Modeli")
+st.write("Veri Gir")
+
+text = st.selectbox('text', df['text'].unique())
+feeling = st.selectbox('feeling', df['feeling'].unique())
+
+    
+if st.button('Predict'):
+    rings = rings_pred(text,feeling)
+    st.write(f'The predicted rings is: {rings:.2f}')

requirements.txt

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+streamlit
+scikit-learn
+pandas
+tensorflow