Our data science doctor provides a hands-on neural networking tutorial to explain how to get started with the popular Keras library, a high-level wrapper over TensorFlow.

At the start of May, I decided to get TensorFlow Developer Certified. So I set myself up with a curriculum to sharpen my skills and took the certification — turns out, I passed. Let me tell you ...

The principal language for using TensorFlow is Python, although there is limited support for C++. The tutorials supplied with TensorFlow include applications for handwritten digit classification ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

If you are adept at Python and remember your high school algebra, you might enjoy [Oliver Holloway’s] tutorial on getting started with Tensorflow in Python.

While it isn’t JavaScript, we did enjoy this Python TensorFlow tutorial. There’s also the very recent video from the TensorFlow Dev Summit, you can watch below.

Overview The right Python libraries can dramatically improve speed, efficiency, and maintainability in 2025 projects.Mastering a mix of data, AI, and web-focuse ...

At the same time, TensorFlow started to play better with standard Python infrastructure such as PyPI and pip, and with the NumPy package widely used by the scientific computing community.

However, the TensorFlow group's recent work with the Raspberry Pi Foundation should make it more straightforward for developers using the Python programming language to build AI applications on ...

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.