坊间传闻：「TensorFlow 适合业界，PyTorch 适合学界」。都 2022 年了，还是这样吗？ 快到 2022 了，你是选 PyTorch 还是 TensorFlow？之前有一种说法：TensorFlow 适合业界，PyTorch 适合学界。这种说法到 2022 年还成立吗？在这篇文章中，作者从模型可用性、部署便捷度和 ...

随着 TensorFlow 2.0 的发布，不少开发者产生了一些疑惑：作为 Keras 用户，TensorFlow 2.0 的发布跟我有关系吗？TensorFlow 中的 tf.keras 和 Keras 有什么区别？我该用哪一个训练神经网络？在本文中，作者给出的答案是：你应该在以后所有的深度学习项目和实验中都使用 tf ...

PyTorch（1.8）和Tensorflow（2.5）最新版本比较。 自深度学习重新获得公认以来，许多机器学习框架层出不穷，争相成为研究人员以及行业从业人员的新宠。从早期的学术成果 Caffe、Theano，到获得庞大工业支持的 PyTorch、TensorFlow，许多研究者面对大量的学习框架不知 ...

PyTorch（1.8）和Tensorflow（2.5）最新版本比较。 自深度学习重新获得公认以来，许多机器学习框架层出不穷，争相成为研究人员以及行业从业人员的新宠。从早期的学术成果 Caffe、Theano，到获得庞大工业支持的 PyTorch、TensorFlow，许多研究者面对大量的学习框架不知 ...

【导读】用PyTorch还是TensorFlow，对于大部分深度学习从业者来说真是一个头疼的问题。最近Reddit上有个帖子从三个方面对比了两个框架，结果竟然是平手？ 你用PyTorch还是用TensorFlow？ 对于不同人群可能有不同的答案，科研人员可能更偏爱PyTorch，因其简单易用 ...

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment The importance of machine learning and deep learning is no longer in ...

Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After ...

TensorFlow was created simply to develop your own machine-learning (ML) models. You might even experience it daily and not know it, like recommendation systems that suggest the next YouTube video, ...

"Thanks to the years of close engineering collaboration between Intel and Google, optimizations in the oneDNN library are now default for x86 CPU packages in TensorFlow. This brings significant ...

Religious wars have been a cornerstone in tech. Whether it’s debating about the pros and cons of different operating systems, cloud providers, or deep learning frameworks — a few beers in, the facts ...