Sentiment Analysys

app.py

@@ -0,0 +1,34 @@
+import streamlit as st
+import tensorflow as tf
+from tensorflow import keras
+import pandas as pd
+import numpy as np
+from PIL import Image
+
+
+from tensorflow.keras.models import load_model
+
+st.set_page_config(page_title = 'Sentiment Analysis Bitcoin',
+                  initial_sidebar_state = "expanded",
+                  menu_items = {
+                      'About' : 'Milestone 2 Fase 2'
+                  })
+
+image = Image.open('bitcoin.png')
+
+# load model
+model = keras.models.load_model("model_bitcoin")
+
+
+label = ['Negative', 'Neutral', 'Positive']
+
+st.title("Sentiment Analysis Bitcoin")
+st.image(image)
+
+news_title = st.text_input('Enter a Tweet Bitcoin')
+new_data = pd.DataFrame([news_title])
+res = model.predict(new_data)
+res = res.argmax()
+press = st.button('Predict')
+if press:
+   st.title(label[res])

requirements.txt

@@ -0,0 +1,6 @@
+streamlit
+pandas
+numpy
+scipy
+tensorflow-cpu
+scikit-learn == 1.0.2