f0nzie

### A Pluto.jl notebook ###
# v0.19.9

using Markdown
using InteractiveUtils

# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
    quote
        local iv = try Base.loaded_modules[Base.PkgId(Base.UUID("6e696c72-6542-2067-7265-42206c756150"), "AbstractPlutoDingetjes")].Bonds.initial_value catch; b -> missing; end

f0nzie

### A Pluto.jl notebook ###
# v0.19.9

using Markdown
using InteractiveUtils

# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
    quote
        local iv = try Base.loaded_modules[Base.PkgId(Base.UUID("6e696c72-6542-2067-7265-42206c756150"), "AbstractPlutoDingetjes")].Bonds.initial_value catch; b -> missing; end

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def sigmoid_derivative(x):
    """
    Compute the gradient (also called the slope or derivative) of the sigmoid function with respect to its input x.
    You can store the output of the sigmoid function into variables and then use it to calculate the gradient.
    
    Arguments:
    x -- A scalar or numpy array

    Return:
    ds -- Your computed gradient.

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def normalizeRows(x):
    """
    Implement a function that normalizes each row of the matrix x (to have unit length).
    
    Argument:
    x -- A numpy matrix of shape (n, m)
    
    Returns:
    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
    """

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# One chunk - Linear Regression in Python

Source: https://medium.com/dsnet/linear-regression-with-pytorch-3dde91d60b50

Notebook: https://jvn.io/aakashns/e556978bda9343f3b30b3a9fd2a25012

```{r}
library(reticulate)
use_condaenv("pytorch37")
py_config()

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#!/home/msfz751/.pyenv/shims/python3
# #!/usr/bin/env python
# change to location of your preferred virtual environment
# Source:
# https://itectec.com/ubuntu/ubuntu-taking-screenshot-of-a-specific-area-from-the-command-line/

import subprocess
import os
import sys

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find_rsuite_root <- function(key = "PARAMETERS")  rprojroot::find_root(key)
source(file.path(find_rsuite_root(), 'R', 'set_env.R'), chdir = TRUE)
.libPaths(c(normalizePath(sbox_path), normalizePath(lib_path), .libPaths()))

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# Digits recognition on PNG images. R code

1. Added utility functions
2. Introspection on dim=2. Extra layers on tensor
3. Converting code from Python to R

## Objectives
1. Read PNG images instead of MNIST standard dataset.
2. Save the model
3. Read an unseen digit as PNG file using the saved model