Rising Odegua risenW

Full Stack Software Engineer | Generalist | Always Curious

risenW / load-model.js

Created July 15, 2020 16:46

	console.log('Loading Model...')
	home_ = process.cwd()
	model_path = "file://"+ home_ + "/model/model.json"
	console.log('Model Loaded Successfull')

risenW / model-load.js

Created July 15, 2020 16:45

	console.log('Loading Model...')
	model = await tf.loadLayersModel("file:///home/Projects/recommender-sys/recommender-books/model/model.json", false);
	console.log('Model Loaded Successfull')

risenW / rec-model-updated.js

Created July 15, 2020 16:44

	const functions = require('firebase-functions');
	const express = require("express");
	const bodyParser = require("body-parser");
	const expressHbs = require("express-handlebars");
	const books = require("./data/web_book_data.json")
	const model = require("./model")

	const app = express();
	app.set("views", "./views");
	app.set("view engine", "hbs");

risenW / rec-emb.py

Created July 14, 2020 08:36

	b_id =list(ratings_df.book_id.unique())
	b_id.remove(10000)
	dict_map = {}
	for i in b_id:
	dict_map[i] = books_df_copy.iloc[i]['title']

	out_v = open('vecs.tsv', 'w')
	out_m = open('meta.tsv', 'w')
	for i in b_id:
	book = dict_map[i]

risenW / rec-hist.py

Created July 14, 2020 08:35

	hist = model.fit([Xtrain.book_id, Xtrain.user_id], Xtrain.rating,
	batch_size=64,
	epochs=5,
	verbose=1,
	validation_data=([Xtest.book_id, Xtest.user_id], Xtest.rating))

risenW / rec-model.py

Created July 14, 2020 08:34

	#Book input network
	input_books = tf.layers.Input(shape=[1])
	embed_books = tf.layers.Embedding(nbook_id + 1,15)(input_books)
	books_out = tf.layers.Flatten()(embed_books)

	#user input network
	input_users = tf.layers.Input(shape=[1])
	embed_users = tf.layers.Embedding(nuser_id + 1,15)(input_users)
	users_out = tf.layers.Flatten()(embed_users)

risenW / split.py

Created July 14, 2020 08:33

	from sklearn.model_selection import train_test_split
	Xtrain, Xtest = train_test_split(ratings_df, test_size=0.2, random_state=1)
	print(f"Shape of train data: {Xtrain.shape}")
	print(f"Shape of test data: {Xtest.shape}")

risenW / rec-index.html

Created July 14, 2020 06:54

	<!DOCTYPE html>
	<html lang="en">

	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<!-- Bootstrap CSS -->
	<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.0/css/bootstrap.min.css"
	integrity="sha384-9aIt2nRpC12Uk9gS9baDl411NQApFmC26EwAOH8WgZl5MYYxFfc+NcPb1dKGj7Sk" crossorigin="anonymous">

risenW / rec-model.js

Last active July 14, 2020 06:40

	const tf = require('@tensorflow/tfjs-node')
	const books = require("./data/web_book_data.json")



	async function loadModel() {
	console.log('Loading Model...')
	model = await tf.loadLayersModel("file:///home/dsn/personal/Tfjs/TensorFlowjs_Projects/recommender-sys/recommender-books/model/model.json", false);
	console.log('Model Loaded Successfull')
	// model.summary()

risenW / rec-recommend.js

Created July 14, 2020 06:06

	app.get("/recommend", (req, res) => {
	let userId = req.query.userId
	if (Number(userId) > 53424 \|\| Number(userId) < 0) {
	res.send("User Id cannot be greater than 53,424 or less than 0!")
	} else {
	recs = model.recommend(userId)
	.then((recs) => {
	res.render("index", { recommendations: recs, forUser: true })
	})
	}