/explore

Click through on any links that interest you or select the planets on the right to continue exploring the Outer Web.
You are here

 www.hamza.se
Neural Networks: Simpler Than You Think | Hamza Khuswan
| | www.paepper.com
Training a neural network with Numpy :: Päpper's Machine Learning Blog - This blog features state of the art applications in ...
0.9 parsecs away

Travel
| | [AI summary] This article explains how to train a simple neural network using Numpy in Python without relying on frameworks like TensorFlow or PyTorch, focusing on the implementation of ReLU activation, weight initialization, and gradient descent for optimization.
| | dennybritz.com
Implementing a Neural Network from Scratch in Python · Denny's Blog
1.1 parsecs away

Travel
| | All the code is also available as an Jupyter notebook on Github.
| | zserge.com
AI or ain't: Neural Networks
1.0 parsecs away

Travel
| | Neural network and deep learning introduction for those who skipped the math class but wants to follow the trend
| | blog.fastforwardlabs.com
"Hello world" in Keras (or, Scikit-learn versus Keras)
9.0 parsecs away

Travel
| This article is available as a notebook on Github. Please refer to that notebook for a more detailed discussion and code fixes and updates. Despite all the recent excitement around deep learning, neural networks have a reputation among non-specialists as complicated to build and difficult to interpret. And while interpretability remains an issue, there are now high-level neural network libraries that enable developers to quickly build neural network models without worrying about the numerical details of floating point operations and linear algebra.