Create app.py

app.py

@@ -0,0 +1,64 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import streamlit as st
+
+#Function definition
+def lossfunction(x):
+    return x**2
+
+#Gradient of the loss function
+def gradient(x):
+    return 2*x
+
+#Gradient descent algorithm
+def gradient_descent(starting_point, learning_rate, iterations):
+    x_values = [starting_point]
+    for _ in range(iterations):
+        gradient_value = gradient(x_values[-1])
+        new_x = x_values[-1] - learning_rate * gradient_value
+        x_values.append(new_x)
+    return x_values
+
+#Streamlit layout
+st.title("Gradient Descent Visualization")
+
+#Sidebar inputs
+st.sidebar.header("Parameters")
+starting_point = st.sidebar.slider("Starting Point", -10.0, 10.0, 5.0, 0.1)
+learning_rate = st.sidebar.slider("Learning Rate", 0.01, 1.0, 0.1, 0.01)
+iterations = st.sidebar.slider("Number of Iterations", 1, 50, 10, 1)
+
+#Perform gradient descent
+x_values = gradient_descent(starting_point, learning_rate, iterations)
+y_values = [loss_function(x) for x in x_values]
+
+#Generate plot
+fig, ax = plt.subplots(figsize=(8, 5))
+x_range = np.linspace(-10, 10, 500)
+y_range = loss_function(x_range)
+
+#Plot the loss function
+ax.plot(x_range, y_range, label="Loss Function", color="blue")
+#Plot the gradient descent steps
+ax.scatter(x_values, y_values, color="red", label="Steps", zorder=5)
+ax.plot(x_values, y_values, color="orange", linestyle="--", label="Gradient Descent Path")
+
+#Annotate points
+for i, (x, y) in enumerate(zip(x_values, y_values)):
+    ax.text(x, y, f"{i}", fontsize=8, ha="right")
+
+ax.set_title("Gradient Descent")
+ax.set_xlabel("x")
+ax.set_ylabel("Loss")
+ax.legend()
+
+#Display in Streamlit
+st.pyplot(fig)
+
+#Display final results
+st.write("### Gradient Descent Results")
+st.write(f"Starting Point: {starting_point}")
+st.write(f"Learning Rate: {learning_rate}")
+st.write(f"Number of Iterations: {iterations}")
+st.write(f"Final x Value: {x_values[-1]:.4f}")
+st.write(f"Final Loss Value: {loss_function(x_values[-1]):.4f}")