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Faisal Al-Tameemi FaisalAl-Tameemi

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View benwillcabinets.service
[Unit]
Description=Ben Will Cabinets
[Service]
ExecStart=/var/www/construction-website/server.js
Restart=always
User=nobody
Group=nogroup
Environment=PATH=/usr/bin:/usr/local/bin
Environment=NODE_ENV=production
@FaisalAl-Tameemi
FaisalAl-Tameemi / build_directory.sh
Last active Sep 5, 2019 — forked from naesheim/buildWhenAffected.sh
CircleCi - only build features that has changed
View build_directory.sh
set -e
# latest commit
LATEST_COMMIT=$(git rev-parse HEAD)
# latest commit where path/to/folder1 was changed
FOLDER1_COMMIT=$(git log -1 --format=format:%H --full-diff path/to/folder1)
# latest commit where path/to/folder2 was changed
FOLDER2_COMMIT=$(git log -1 --format=format:%H --full-diff path/to/folder2)
View results-xgboost-linear-reg.csv
Model Name Training Score Validation Score Test Score
NaiveModel (always predicts mean price) 0.000000 -0.000172 -0.000609
RandomForestRegressor 0.711069 0.487592 0.489714
PLSRegression 0.459397 0.445175 0.432827
LinearRegression 0.534462 0.488490 0.487435
View train-test.py
def train_test(df, response_col='price', dummy_na=False, test_size=.3, rand_state=42, plot=False):
#Split into explanatory and response variables
X = df.drop(response_col, axis=1)
y = df[response_col]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=rand_state)
lm_model = LinearRegression(normalize=True)
lm_model.fit(X_train, y_train)
View coeffecients-linear-model.csv
Feature Coeffecient Absolute Coeffecient
neighbourhood_Waterfront Communities-The Island 82.96 82.96
neighbourhood_Beechborough-Greenbrook 82.35 82.35
neighbourhood_Bay Street Corridor 66.44 66.44
neighbourhood_Church-Yonge Corridor 64.54 64.54
room_type_Shared room -64.34 64.34
View most-expensive-price-per-bed-neighbourhoods-airbnb-toronto.csv
Neighbourhood Average Listing Price ($) Average Price per Bed ($)
Waterfront Communities-The Island 191.83 124.92
Rosedale-Moore Park 174.61 117.98
Niagara 158.23 114.36
Bridle Path-Sunnybrook-York Mills 166.33 114.02
Bay Street Corridor 147.45 107.69
View top-listings-count-airbnb-toronto.csv
Neighbourhood Listings Count on AirBnB
Waterfront Communities-The Island 3093
Niagara 799
Annex 691
Church-Yonge Corridor 589
Dovercourt-Wallace Emerson-Junction 512
Little Portugal 493
Bay Street Corridor 491
Trinity-Bellwoods 449
Kensington-Chinatown 442
View most-expensive-neighbourhoods-airbnb-toronto.csv
Neighbourhood Average Listing Price ($) Average Price per Bed ($)
Waterfront Communities-The Island 191.83 124.92
Rosedale-Moore Park 174.61 117.98
Lawrence Park South 168.72 79.51
Bridle Path-Sunnybrook-York Mills 166.33 114.02
Lawrence Park North 164.93 68.55
@FaisalAl-Tameemi
FaisalAl-Tameemi / erc721-example.sol
Created Apr 21, 2018 — forked from aunyks/erc721-example.sol
My implementation of the ERC721 token standard. WARNING: THIS CODE IS FOR EDUCATIONAL PURPOSES. DO NOT DEPLOY TO THE NETWORK.
View erc721-example.sol
pragma solidity ^0.4.19;
contract ERC721 {
string constant private tokenName = "My ERC721 Token";
string constant private tokenSymbol = "MET";
uint256 constant private totalTokens = 1000000;
mapping(address => uint) private balances;
mapping(uint256 => address) private tokenOwners;
mapping(uint256 => bool) private tokenExists;
mapping(address => mapping (address => uint256)) private allowed;
mapping(address => mapping(uint256 => uint256)) private ownerTokens;
View kovan.txt
0x69b8Fb504E2eb0B2A8B6e5C1caF4ce6070c76BDB