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Hello, Julia!

What I learnt and implemented

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Hey! This post is about my introduction to the world of Julia. I took this challenge of learning Julia and making something in it. Since Julia is pretty similar to Python, I made a hypothesis. That is can I learn julia and be up and running with something in two days? What I realised is, if you're from a python background and have some expereince in it, then learning Julia is going to be fun and breezy for you. So, here I am after my two day rendezvous with Julia.

So, what I used to learn Julia?
I used resources from julia academy

What did I implement?
I decided to go for one the resources I learnt deep learning from: Neural Networks and Deep Learning

Impemented the Julia version of Week 2 assignment of Neural Networks and Deep Learning course.

I hope it's useful to you. It was a lot of fun and I am in love with Julia ❤

Let's begin!

using Random
using Plots
using HDF5
using Statistics
using Base.Iterators

Load dataset

  1. There are two files: train_catvnoncat.h5 & test_catvnoncat.h5
  2. According to our notation, X is of shape (num_features, num_examples) & y is a row vector of shape (1, num_examples).
  3. We write a function load_dataset() which:
    • Takes in HDF5 files
    • Converts them into Array{Float64, 2} arrays.
    • Reshapes them according to our notation & returns X_train, y_train, X_test, y_test
function load_dataset(train_file::String, test_file::String)
    
    X_train = convert(Array{Float64, 4}, h5read(train_file, "train_set_x"))
    y_train = convert(Array{Float64, 1}, h5read(train_file, "train_set_y"))
    
    X_test = convert(Array{Float64, 4}, h5read(test_file, "test_set_x"))
    y_test = convert(Array{Float64, 1}, h5read(test_file, "test_set_y"))
    
    num_features_train_X = size(X_train, 1) * size(X_train, 2) * size(X_train, 2)
    num_features_test_X = size(X_test, 1) * size(X_test, 2) * size(X_test, 2)
    
    X_train = reshape(X_train, (num_features_train_X, size(X_train, 4)))
    y_train = reshape(y_train, (1, size(y_train, 1)))
    
    X_test = reshape(X_test, (num_features_test_X, size(X_test, 4)))
    y_test = reshape(y_test, (1, size(y_test, 1)))
    
    X_train, y_train, X_test, y_test
    
end
load_dataset (generic function with 1 method)