近年来人工智能火爆出圈，无数人怀揣着“学会Python就能入行AI”的憧憬涌入这个领域。然而，当满怀激情的你刷完了Python语法、跑通了几个开源项目，却发现在真正的面试或工作中寸步难行——这是为什么？因为仅凭Python基础，你很容易掉进以下几个“天坑”。

Around the Hackaday secret bunker, we’ve been talking quite a bit about machine learning and neural networks. There’s been a lot of renewed interest in the topic recently because of the success of ...

It's possible to create neural networks from raw code. But there are many code libraries you can use to speed up the process. These libraries include Microsoft CNTK, Google TensorFlow, Theano, PyTorch ...

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 ...

Google's open source framework for machine learning and neural networks is fast and flexible, rich in models, and easy to run on CPUs or GPUs What makes Google Google? Arguably it is machine ...

Machine learning is an integral part of what powers our online existences. It’s the technology that helps suggest new Facebook friends and impulse purchases on Amazon. And also a field that Google, ...

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker News ...