View generate_passwords.jl
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# Generate Passwords in Julia | |
# Source: https://github.com/logankilpatrick/10-Julia-Projects-for-Beginners | |
using ProgressBars | |
using Random | |
# WARNING: Do not use this code to generate actual passwords! | |
function generate_passwords() | |
num_passwords = parse(Int64, Base.prompt("How many passwords do you want to generate?")) | |
password_length = parse(Int64, Base.prompt("How long should each password be?")) |
View rock_paper_scissors.jl
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# Rock 🗿, Paper 📃, Scissors ✂️ Game in Julia | |
function play_rock_paper_scissors() | |
moves = ["🗿", "📃", "✂️"] | |
computer_move = moves[rand(1:3)] | |
# Base.prompt is similar to readline which we used before | |
human_move = Base.prompt("Please enter 🗿, 📃, or ✂️") | |
# Appends a ": " to the end of the line by default |
View number_guess_computer.jl
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# Computer Number Guessing Game in Julia | |
# Source: https://github.com/logankilpatrick/10-Julia-Projects-for-Beginners | |
using Random | |
function play_number_guess_computer() | |
print("Please enter a number between 1 and 50 for the computer to try and guess: ") | |
# Take in the user input and convert it to a number |
View number_guess_human.jl
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# Number Guessing Game in Julia | |
# Source: https://github.com/logankilpatrick/10-Julia-Projects-for-Beginners | |
function play_number_guess_human() | |
total_numbers = 25 # | |
# Generate a random number within a certain range | |
target_number = rand(1:total_numbers) | |
guess = 0 |
View madlibs.jl
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# Mad Libs in Julia | |
# Source: https://github.com/logankilpatrick/10-Julia-Projects-for-Beginners | |
function play_mad_libs() | |
print("Enter a verb (action): ") | |
verb1 = readline() | |
print("Enter an adjective (descriptive word): ") | |
adj1 = readline() |
View dense.py
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import os | |
import sys | |
import numpy as np | |
from tensorflow.keras import models, layers | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.optimizers import Adam | |
from tensorflow.keras.datasets import mnist | |
# Change this to the location of the database directories | |
DB_DIR = os.path.dirname(os.path.realpath(__file__)) |
View cnn_model.py
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import os | |
import sys | |
import numpy as np | |
from tensorflow.keras import models, layers, callbacks | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.optimizers import Adam | |
from tensorflow.keras.datasets import mnist | |
# Change this to the location of the database directories | |
DB_DIR = os.path.dirname(os.path.realpath(__file__)) |
View cnn_model_with_transformations.py
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import os | |
import sys | |
import numpy as np | |
from tensorflow.keras import models, layers, callbacks | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.optimizers import Adam | |
from tensorflow.keras.datasets import mnist | |
from matplotlib import pyplot as plt | |
# Change this to the location of the database directories |
View RELU.py
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import os | |
import sys | |
from typing import Counter | |
import tensorflow as tf | |
import numpy as np | |
from tensorflow.keras import models, layers, callbacks | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.optimizers import Adam | |
from tensorflow.keras.datasets import mnist | |
from matplotlib import pyplot as plt |
View LSTM.py
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import os | |
import sys | |
import numpy as np | |
import tensorflow as tf | |
from tensorflow.keras import models, layers, callbacks | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.optimizers import Adam | |
from tensorflow.keras.datasets import mnist | |
# Change this to the location of the database directories |
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