Python - tensorflow.math.bessel_i0e() function Last Updated : 22 Feb, 2023 Comments Improve Suggest changes Like Article Like Report TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. bessel_i0e() is function present in tensorflow math module. This function is used to find element wise exponentially scaled modified 0 order Bessel function. bessel_i0e(x) = exp(-abs(x)) bessel_i0(x) bessel_i0e(x) is faster and numerically stabler than bessel_i0(x). Syntax: tensorflow.math.bessel_i0e( x, name) Parameters: x: It's a tensor and the allowed dtypes for this tensor are bfloat16, half, float32, float64.name: It is an optional argument which is used to give operation name. Returns: It returns a tensor or sparse tensor depending upon x of same dtype as x. Example 1: Python3 # importing the library import tensorflow as tf # initializing the input a = tf.constant([1,2,3,4,5], dtype = tf.float64) # printing the input print('a: ',a) # evaluating the result r = tf.math.bessel_i0e(a) # printing the result print("Result: ",r) Output: a: tf.Tensor([1. 2. 3. 4. 5.], shape=(5,), dtype=float64) Result: tf.Tensor([0.46575961 0.30850832 0.24300035 0.20700192 0.18354081], shape=(5,), dtype=float64) Example 2: Visualization Python3 # importing the library import tensorflow as tf import matplotlib.pyplot as plt # initializing the input a = tf.constant([1,2,3,4,5], dtype = tf.float64) # evaluating the result r = tf.math.bessel_i0e(a) #plotting the graph plt.plot(a, r, color = 'green', marker = "o") plt.title("tensorflow.math.bessel_i0e") plt.xlabel("Input") plt.ylabel("Result") plt.show() Output: Comment More infoAdvertise with us Next Article Introduction to Machine Learning A aman neekhara Follow Improve Article Tags : Machine Learning AI-ML-DS With Python Practice Tags : Machine Learning Similar Reads Machine Learning Tutorial Machine learning is a branch of Artificial Intelligence that focuses on developing models and algorithms that let computers learn from data without being explicitly programmed for every task. 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