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README.md

@@ -1,10 +1,10 @@
 ---
 title: Titanic
-emoji: 📈
-colorFrom: red
-colorTo: red
+emoji: 💻
+colorFrom: blue
+colorTo: pink
 sdk: gradio
-sdk_version: 3.10.1
+sdk_version: 3.8.2
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

@@ -0,0 +1,50 @@
+import gradio as gr
+import numpy as np
+import hopsworks
+import joblib
+
+project = hopsworks.login()
+fs = project.get_feature_store()
+
+
+mr = project.get_model_registry()
+model = mr.get_model("titanic_modal", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/titanic_model.pkl")
+
+
+def titanic(pclass, sex, age, sibsp, parch, pricerange):
+    input_list = []
+    input_list.append(pclass)
+    input_list.append(sex)
+    input_list.append(age)
+    input_list.append(sibsp)
+    input_list.append(parch)
+    input_list.append(pricerange)
+    # 'res' is a list of predictions returned as the label.
+    res = model.predict(np.asarray(input_list).reshape(1, -1))
+    if res[0]==0:
+        output = "Did not survive"
+    else:
+        output = "Survived"
+
+    return output
+
+demo = gr.Interface(
+    fn=titanic,
+    title="Titanic Predictive Analytics",
+    description="Experiment with passenger information to predict if the passenger survived or not",
+    allow_flagging="never",
+    inputs=[
+        gr.inputs.Number(default=1, label="ticket class (1 = 1st, 2 = 2nd, 3 = 3rd)"),
+        gr.inputs.Number(default=0, label="sex (0=male, 1=female)"),
+        gr.inputs.Number(default=24, label="age (years)"),
+        gr.inputs.Number(default=1.0, label="# of siblings/spouses aboard"),
+        gr.inputs.Number(default=1.0, label="# of children/parents aboard"),
+        gr.inputs.Number(default=1.0, label="pricerange (1=cheapest, 5=most expensive)"),
+        ],
+    outputs="text")
+
+
+demo.launch()
+

requirements.txt

@@ -1,7 +1,4 @@
+hopsworks
 joblib
 scikit-learn
-seaborn
-xgboost
-dataframe-image
-modal-client
-gradio
+pillow