Big Data Digest article, see the end of the article for reposting requirements Author | Brandon Amos Translation | Molly, Han Xiaoyang Table of Contents ■ Introduction ■ Step 1: Understanding Images as Samples from a Probability Distribution How do you fill in missing information? But how do you start with statistics? These are all … Read more
Google has many GDEs (Google Developers Experts) around the world, all of whom are recognized experts by Google. GDEs are committed to spreading and promoting new technologies in various forms and helping developers solve problems encountered during the development process. Each GDE has made special contributions to their respective fields. The author of “A Simple … Read more
By / Wang Shuhao 1. The Intelligent Path to Pathological Diagnosis According to the World Health Organization (WHO), malignant tumors are the second leading cause of death globally, causing nearly ten million deaths each year. The diagnosis of malignant tumors requires sufficient evidence, with histopathological diagnosis being the most reliable method for tumor diagnosis, serving … Read more
By / Aakanksha Chowdhery, Software Engineer Why don’t you get a response when you say “Yo Google” to Google Assistant? After all, it’s only one word different from “Ok Google”. This is because Google Assistant recognizes only these two words as ‘wake words’. Wake words are crucial for low-power machine learning design, where models with … Read more
By / AMD Deep Learning Software Director Mayank Daga We are excited to announce the launch of TensorFlow v1.8 for ROCm GPUs, which includes the Radeon Instinct MI25. This is a significant milestone for AMD’s ongoing deep learning acceleration efforts. ROCm, which stands for Radeon Open Ecosystem, is our open-source software foundation for GPU computing … Read more
By / Li Xihan, Google Developers Expert This article is excerpted from “Simple and Brutal TensorFlow 2”, reply “Manual” to get the collection. It should have been introduced long ago, the deep reinforcement learning in TensorFlow, yes, it is finally done! This article will introduce the process of implementing the Q-learning algorithm using TensorFlow in … Read more
Guest Blog Author: Dr. Erwin John T. Carpio As a physician and radiologist, I have always wanted to learn and develop machine learning models and apply them to my field. However, machine learning felt like a foreign language to me, and with my limited programming experience and non-computer science background, I thought it was challenging … Read more
Whether you are on your way to TensorFlow World or unable to attend in person, read below for the latest information on the demonstrations and experience the new GitHub codebase.You can also follow #MissionToTensorFlowWorld on Twitter for real-time experiences! Half a century ago, the Apollo 11 mission realized humanity’s dream of landing on the moon. … Read more
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