Written by / TensorFlow Model Optimization Team We are pleased to announce the release of the Quantization Aware Training (QAT) API, which is part of the TensorFlow Model Optimization Toolkit. With QAT, you can leverage the advantages of quantization in performance and size while maintaining accuracy close to the original. This work is part of … Read more
Written by / Li Xihan, Google Developers Expert This article is excerpted from “Simple and Rough TensorFlow 2.0” TensorBoard: Visualizing the Training Process Sometimes, you want to observe the changes of various parameters during the model training process (for example, the value of the loss function). While you can check this through command line output, … Read more
Authorized Reprint from OReillyData Author | Raul Puri et al. How to Build and Train an Image Captioning Generator Using TensorFlow The image captioning model combines advances in computer vision and machine translation in recent years, using neural networks to generate captions for real images. For a given input image, the neural image captioning model … Read more
1 New Intelligence Column Author: Liu Shiqiang [New Intelligence Guide] This article introduces the application of deep learning methods in the field of image translation by implementing an encoding-decoding “image translator” for image enhancement, showcasing the effectiveness of deep learning applications in image translation. In recent years, deep learning has achieved remarkable results in image … Read more
Machine Heart Column Author: Principal Engineer Dong Bingfeng, Chubao AI Lab The input vector X in traditional CRF is generally in the one-hot format of words, which loses a lot of semantic information about words. With the advent of word embedding methods, the word representation in vector form generally performs better than the one-hot representation. … Read more
Organized by Machine Heart Author：Wan Zhen Contributors: Machine Heart Editorial Team Andrew Ng’s DeepLearning.ai has released its final course on January 31. Recently, Wan Zhen from Chongqing University created a set of notes on the deep learning specialization course, which explains key concepts and assignment codes in detail, starting from the basics of neural networks … Read more
Scan the QR code in the image to join the technology English live broadcast. Students interested in Andrew Ng’s latest deep learning course can take a look at this article first. Many people believe that machine learning is too specialized and has a high entry barrier. However, it has been proven that machine learning is … Read more
Selected from Medium Author: Ryan Shrott Editor: Machine Heart The author of this article, Ryan Shrott, Chief Analyst at the National Bank of Canada, has completed all deep learning courses released by Andrew Ng on Coursera to date (as of October 25, 2017) and provides us with insights into the courses. Among the courses available … Read more
Google Vertex AI is a comprehensive platform designed to help developers, data scientists, and businesses easily build, deploy, and manage machine learning and artificial intelligence models. Below is a detailed guide on what Vertex AI is and how to get started with it. What is Google Vertex AI? Vertex AI is an integrated platform that … Read more
Training a Stable Diffusion model is a complex and resource-intensive process that typically requires significant computational resources, such as GPUs or TPUs, and can take considerable time. The training process involves multiple steps, including environment setup, data preparation, model configuration, and training parameter adjustment. First, environment setup is the foundation for training a Stable Diffusion … Read more