The global deep learning systems market is expected to reach $93.34 billion by 2028, with a compound annual growth rate of 39.1%. Deep learning, also known as deep neural learning, is a subset of machine learning and an application of artificial intelligence, where machines mimic the working of the human brain and use artificial neural … Read more
Installing TensorFlow on Windows Installing Python First, you need to install Python on your Windows system. It is recommended to use the official Python distribution, which is Anaconda, as it comes with many scientific computing libraries, such as numpy and scipy, which are also used in TensorFlow. You can download and install Anaconda from the … Read more
In the previous article, I introduced how to perform data parallelism with multiple GPUs in TensorFlow. In this article, I will discuss how to debug TensorFlow models. Compared to regular Python code, debugging TensorFlow code can be relatively difficult due to the symbolic nature of TensorFlow. Here, I will introduce some debugging tools included in … Read more
Commonly used image segmentation loss functions include binary cross-entropy, dice coefficient, Tversky, and Focal Loss. Today, I will reproduce the above loss functions in TensorFlow and compare the results. 1. Cross Entropy The cross-entropy loss function compares the predicted class values with the target values on a pixel-by-pixel basis, and then averages the values over … Read more
Deep Learning Frameworks Author: Horace He Revise: louwill source: https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/ For many practitioners in the deep learning industry, mastering one or more deep learning frameworks is one of the essential skills for daily work. After a period of chaos in the deep learning framework market, a dominant market structure has gradually formed with TensorFlow and … Read more
Click on the above“Beginner Learning Vision” to choose to addStar or “Pin” Important content delivered at the first time Introduction One of the most common uses of TensorFlow and Keras is image recognition/classification. Through this article, you will learn how to achieve this using Keras. Definition If you do not understand the basic concepts of … Read more
Follow the public account “ML_NLP” Set as “Starred”, heavy content will be delivered first! Source | Machine Heart “The official documentation is messy, the search function is difficult to use, and the API is hideous…” This is the complaint of many people about the TensorFlow official documentation. But complaints aside, in the industry, you cannot … Read more
This article introduces how to build a simple neural network using Python 3.0 and TensorFlow 2.0 framework for basic image recognition. 1 Import Dataset from tensorflow import keras fashion_mnist = keras.datasets.fashion_mnist #devide the data into training and test: #train 60000 and test 10000 (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data() This code imports the MNIST image … Read more
Deep learning stands out in artificial intelligence, and to learn deep learning, one must first master an effective deep learning framework. This article will review the currently popular deep learning frameworks worldwide, enhancing everyone’s understanding of these frameworks based on their popularity and application scenarios. Without further ado, here is a chart showing the activity … Read more
Click the above “Beginner Learning Vision” to select Star or Pin. Important content delivered promptly This article is transferred from | Computer Vision Alliance Overview tf.distribute.Strategy is a TensorFlow API used to distribute training across multiple GPUs, multiple machines, or TPUs. With this API, you can distribute existing models and training code with minimal code … Read more