neural-net | An educational neural net library in Rust | Machine Learning library

I am trying to implement Neural Network from scratch. By default, it works as i expected, however, now i am trying to add L2 regularization to my model. To do so, I need to change three methods-

cost() #which calculate cost, cost_derivative , backward_prop # propagate networt backward

You can see below that, I have L2_regularization = None as an input to the init function

I have a .csv database file which looks like this:

I'm trying to study the neural-network-and-deep-learning (http://neuralnetworksanddeeplearning.com/chap1.html). Using the updated version for Python 3 by MichalDanielDobrzanski (https://github.com/MichalDanielDobrzanski/DeepLearningPython). Tried to run it in my command console and it gives an error below. I've tried uninstalling and reinstalling setuptools, theano, and numpy but none have worked thus far. Any help is very appreciated!!

Here's the full error log:

I am new to PyTorch and Machine Learning so I try to follow the tutorial from here: https://medium.com/@nutanbhogendrasharma/pytorch-convolutional-neural-network-with-mnist-dataset-4e8a4265e118

By copying the code step by step I got the following error for no reason. I tried the program on another computer and it gives syntax error. However, my IDE didn't warn my anything about syntax. I am really confused how I can fix the issue. Any help is appreciated.

I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder.

I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder.

I am trying to create an NLP neural-network using the following code:

imports:

I'm trying to figure out how to use the request function of the http and https built-in modules in Node JS (I am aware of third-party wrappers but I'm trying to figure it out myself). I'm running into an issue where the Buffer data from the Response is partially cut off at the end. The issue does not occur when testing with cURL.

Here is the code I've been using:

I'm trying to learn how keras.layers.SimpleRNN works by following a relatively straightforward tutorial (https://machinelearningmastery.com/understanding-simple-recurrent-neural-networks-in-keras/). However, this tutorial assumes the input is scalar, and I've been unable to scale this to higher-dimensional inputs. Here is my attempt to reproduce the behaviour of a simple RNN with 1x2 input for 3 time steps: