Neural Network from Scratch in TensorFlow
9982 ya inscrito
9982 ya inscrito
In this 2-hours long project-based course, you will learn how to implement a Neural Network model in TensorFlow using its core functionality (i.e. without the help of a high level API like Keras). You will also implement the gradient descent algorithm with the help of TensorFlow's automatic differentiation. While it’s easier to get started with TensorFlow with the Keras API, it’s still worth understanding how a slightly lower level implementation might work in tensorﬂow, and this project will give you a great starting point. In order to be successful in this project, you should be familiar with python programming, TensorFlow basics, conceptual understanding of Neural Networks and gradient descent. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Artificial Neural Network
En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:
Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.
En un video de pantalla dividida, tu instructor te guía paso a paso
por BP10 de jul. de 2020
Good for intermediate. But, a little hard for Begineer.
por CB21 de may. de 2020
It's the first time I built the model from scratch instead of using a library, it was fun :)
por DK8 de may. de 2020
It is a good course to know about the neural networks using tensorflow.
por AR3 de jul. de 2020
Best hands-on experience.
The understanding was awesome. Keep making these types of projects.