Quant, Finance, Machine Learning, AI, TensorFlow.
-tf.reduce_mean(mixture_model.log_prob(data)) #assign the optimizer optimizer = tf.optimizers.Adam(learning_rate = 0.01) #train the model for i in range(1000): with tf.GradientTape() as tape: tape.watch([p1, mu1, scal1, mu2, scal2]) loss = negative_log_likelihood(data) gradients =