Hello everyone i have a quantum computing task but i want to analyze this code in AWS BRAKET. how can i run this code in AWS BRAKET SV1. How to create circuit for this problem. How to initiliaze the circuit and device. Thank you

def quantum_algorithm(x_train, y_train, x_test, y_test):
    print("Quantum algorithm is started")
    print("Finding features")
    
    num_features = x_train.shape[1]
    
    # Drawing circuit diagram
    feature_map = ZZFeatureMap(feature_dimension=num_features, reps=1)
    feature_map.decompose().draw(output="mpl", style="clifford", fold=20)
    
    print("Drawing ansatz circuit")
    ansatz = RealAmplitudes(num_qubits=num_features, reps=3)
    ansatz.decompose().draw(output="mpl", style="clifford", fold=20)
    
    optimizer = COBYLA(maxiter=100)
    sampler = Sampler()
    
    objective_func_vals = []
    plt.rcParams["figure.figsize"] = (12, 6)
    
    def callback_graph(weights, obj_func_eval):
        clear_output(wait=True)
        objective_func_vals.append(obj_func_eval)
        plt.title("Objective function value against iteration")
        plt.xlabel("Iteration")
        plt.ylabel("Objective function value")
        plt.plot(range(len(objective_func_vals)), objective_func_vals)
        plt.show()
        
    vqc = VQC(sampler=sampler, feature_map=feature_map, ansatz=ansatz, optimizer=optimizer, callback=callback_graph)
    
    # Clear objective value history
    objective_func_vals = []
    
    start = time.time()
    print("Learning is started")
    vqc.fit(x_train, y_train)
    elapsed = time.time() - start
    
    print(f"Training time: {round(elapsed)} seconds")
    
    # Predict on train and test datasets
    y_train_pred = vqc.predict(x_train)
    y_test_pred = vqc.predict(x_test)