In this post, we'll learn how to integrate TensorFlow.js with MongoDB in Node.js. We'll cover the following topics:
TensorFlow.js is a JavaScript library for training and deploying machine learning models. It's developed by Google and released under the Apache 2.0 open source license.
TensorFlow.js can be used in a variety of ways, including:
MongoDB is a powerful document-oriented database system. It's developed by MongoDB, Inc. and released under the GNU Affero General Public License.
MongoDB can be used in a variety of ways, including:
Before we can integrate TensorFlow.js with MongoDB, we need to install both TensorFlow.js and MongoDB.
There are two ways to install TensorFlow.js:
You can use a script tag to include the TensorFlow.js library in your HTML file.
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.13.3/dist/tf.min.js"></script>
If you're using a package manager like npm or yarn, you can install TensorFlow.js with the following command:
npm install @tensorflow/tfjs
There are two ways to install MongoDB:
You can use a script to install MongoDB. The script will download and install MongoDB for you.
curl -O https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-4.2.2.tgz
tar -zxvf mongodb-osx-x86_64-4.2.2.tgz
mkdir -p mongodb
cp -R -n mongodb-osx-x86_64-4.2.2/ mongodb
If you're using a package manager like Homebrew, you can install MongoDB with the following command:
brew install mongodb
Now that we have TensorFlow.js and MongoDB installed, we can start integrating them.
To do this, we'll need to do the following:
The first thing we need to do is install the MongoDB Node.js driver. We can do this with the following command:
npm install mongodb
Next, we need to connect to the MongoDB database. We can do this with the following code:
const MongoClient = require('mongodb').MongoClient;
const url = 'mongodb://localhost:27017';
MongoClient.connect(url, { useNewUrlParser: true }, (err, client) => {
if (err) throw err;
const db = client.db('test');
console.log('Connected to MongoDB');
});
Now that we're connected to the MongoDB database, we need to create a schema. We can do this with the following code:
const schema = new mongoose.Schema({
name: String,
age: Number,
gender: String
});
Now that we have a schema, we can train a model. We can do this with the following code:
const model = tf.sequential();
model.add(tf.layers.dense({ units: 1, inputShape: [1] }));
model.compile({ loss: 'meanSquaredError', optimizer: 'sgd' });
const xs = tf.tensor2d([1, 2, 3, 4], [4, 1]);
const ys = tf.tensor2d([1, 3, 5, 7], [4, 1]);
model.fit(xs, ys, { epochs: 10 }).then(() => {
model.predict(tf.tensor2d([5], [1, 1])).print();
});
Finally, we need to deploy the model. We can do this with the following code:
const express = require('express');
const app = express();
const port = 3000;
app.use(express.static('public'));
app.get('/', (req, res) => {
res.sendFile(__dirname + '/index.html');
});
app.listen(port, () => console.log(`Listening on port ${port}`));
In this post, we've learned how to integrate TensorFlow.js with MongoDB in Node.js. We've covered the following topics:
If you have any questions or comments, please feel free to leave them below.