Written by / Li Xihan, Google Developers Expert This article is excerpted from “Simple and Rough TensorFlow 2.0” In the previous article, we introduced the widely used convolutional neural networks in the field of images and their implementation in TensorFlow 2.0. This article continues to introduce another widely popular neural network architecture, namely the recurrent … Read more
By / Google TensorFlow Team TensorFlow has evolved into one of the most popular and widely adopted machine learning platforms in the world, and we sincerely thank all the developers and their contributions who have supported us along the way: Researchers: (Predicting earthquake aftershocks, detecting prostate cancer …… ) Developers: (Identifying diseased plants, applications to … Read more
By / Goldie Gadde and Nikita Namjoshi, TensorFlow TensorFlow 2.4 has been officially released! With increased support for distributed training and mixed precision, along with the introduction of a new NumPy frontend and tools for monitoring and diagnosing performance bottlenecks, this version highlights new features and enhancements in performance and scalability. New Features of tf.distribute … Read more
Many tutorials online teach how to install the TensorFlow GPU version, but many beginners have computers with average performance and do not have NVIDIA graphics cards. So how can one learn TensorFlow? This article will guide you step by step to install the TensorFlow CPU version. 1. Preparation Basic requirements: You should at least have … Read more
Abstract This article establishes a data-driven model for predicting f-CaO in clinker using a fully connected neural network based on the TensorFlow+Keras deep learning framework. The model is trained with the Nadam optimizer, showing better robustness compared to SGD (Stochastic Gradient Descent). Furthermore, this article introduces the implementation method for real-time prediction of f-CaO content … Read more
For academic sharing only, does not represent the stance of this public account. Contact for removal if infringing.Reprinted from:Author丨Yukyin@ZhihuSource丨https://zhuanlan.zhihu.com/p/279401802Editor丨Extreme City Platform I recently got a 3090 and found that the various environment configurations written online are quite chaotic and slow. So I tested the fastest 3090 configuration environment myself, feel free to add more! Basic … Read more
Traditional linear models struggle to solve multivariable or multi-input problems, while neural networks like LSTM excel at handling multiple variables. This characteristic makes them useful for addressing time series prediction issues. In the following article, you will learn how to build an LSTM model using the deep learning library Keras to tackle multivariable time series … Read more
Source: Big Data DigestThis article is approximately 4800 words, suggested reading time 10 minutes. This article introduces a code simulation of playing Blackjack, transitioning from a naive strategy to deep learning. Blackjack, also known as 21, originated in France and has a long history that has spread worldwide.With the development of the Internet, Blackjack has … Read more
Author: Adrian Rosebrock Translated by: Wu Zhendong Proofread by: Zhang Damin This article is about 8000 words, and it is recommended to read for 10+minutes. This article will tell you how to use image-based adversarial attacks to disrupt deep learning models, leveraging the Keras and TensorFlow deep learning libraries to implement your own adversarial attacks.[ … Read more
Author: Chen ZhiyanThis article is about 3500 words, and it is recommended to read in 5 minutes This article introduces several very useful deep learning frameworks, their advantages and applications. By comparing each framework, developers can learn how to selectively use them to efficiently and quickly complete project tasks. For beginners in data science, using … Read more