Amazon EFS, Amazon EBS, and Amazon S3 are AWS’ three different cloud storage types that can be applied for different types of workload needs. Let’s take a closer look at the key features of each option, as well as the similarities and differences. Amazon EBS delivers high-availability block-level storage volumes for Amazon Elastic Compute Cloud (EC2) instances. It stores data on a file...
How to Setup SSH Tunneling in Mac OS (or Ubuntu)
When working with Jupyter notebooks on AWS, I want to interact with it directly in my browsers. In order to do so, we may need to create an SSH tunnel from our laptop to the remote server. If you are using a Macbook, you can easily do so using the default Terminal application available in the Mac OS. Yes, we do not have to install any other application for doing so, as we do in Windows. If you...
Play with computer vision using teachable machine
Nowadays, with the existing tools, creating an AI application is not so complicated. In this post, I will quickly show how easy you can make a computer vision project within 10 minutes. Steps Create a computer vision project in Teachable machinePrepare some images of different classes, e.g. cup, people, hand.Upload photos and train the modelDownload the model and integrate to your website (web...
deep learning: Linear Autoencoder with Keras
This post introduces using linear autoencoder for dimensionality reduction using TensorFlow and Keras. What is a linear autoencoder An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction, by training the network...
Recurrent neural network – predict monthly milk production
In part 1, we introduced a simple RNN for time-series data. To continue, this article applies a deep version of RNN on a real dataset to predict monthly milk production. The data Monthly milk production: pounds per cow. Jan 1962 – Dec 1975. You can download the data using this link. Download: CSV file The data contains the production of 168 months (14 years). We will use an RNN to predict...