Technology

In this mini-series of posts, I will describe a hyper-parameter tuning experiment on the fashion-mnist dataset. I wanted to test out a guided and easy way to run hyper-parameter tuning. In Part II, I described setting up the end-to-end pipeline with a baseline, and running hyper-parameter tuning with the hyperopt package. In this third and final chapter, I describe my target models, a convolutional neural network trained from scratch and a transfer learning model. ...

In this mini-series of posts, I will describe a hyper-parameter tuning experiment on the fashion-mnist dataset. In the Part I, I described the workflow to create the data for my experiments. In this post, I describe creating the baseline and a guided hyper-parameter tuning method. The Baseline For any modeling tasks, I always like to create a baseline model as a starting point. Typically, this will be a relatively basic model in nature. This serves three very important purposes: ...

In this mini-series of posts, I will describe a hyper-parameter tuning experiment on the fashion-mnist dataset. Hyper-paramater tuning is a very important aspect of training models in machine learning. Particularly with neural networks, where the architecture, optimizer and data can be subject to different parameters. When developing machine learning solutions, there is an interative cycle that can be adopted to enable fast iteration, continous targeted improvements, and testing of the solution - as with any other software systems problems. However, in practice, those iterations can cease as soon as there is a workable solution is in place. And more often than not, that workable solution runs on an initial guess of the right paramters. Thus, little to no hyper-paramter tuning takes place. ...

In this May’s edition of “These Past Weeks in Science & Tech”, I’ll be discussing /R Biological Data Stores Our bodies are walking a library of information. From chemical processes that regulate our biological functions, to experiences imprinted in our minds through exeprience, our cells somehow manage to store, access, and use information. So, it is no surpise that we should turn to biology to find the next generation of storage. Researchers Yaniv Erlich, from Columbia University, and Dina Zielinski the New York Genome Center, have come up with a method to successfully convert binary data into DNA strands, storing up to 2MB. ...

I tend to read quite a bit. I read journals, blogs, and sites on technology, AI, learning (with and without machines), and technology. These include renowed ones, like ACM Tech News, MIT News and Technology Review, and aleatory ones that I find on the web through platforms like Medium. As someone who enjoys reading, and writing, I figured I could use summary notes on the things I learn about. And so, I decided to do that on this blog. This is the first edition of what I am labeling as a “summary notes” type of posts, which I will be writing every few weeks. ...

Pokémon Go has been released for roughly six weeks now, and it’s already a phenomenon that is moving people. Literally. Whether you’re trying to get an egg hatched, searching for new Pokémon to capture, or just looking for the next gym battle to conquer your turf, and territory, people are out and about with their Pokédex in hand walking the Earth. It’s a must, if you want to become the world’s most premier Pokémon master; and according to the number of users of the app, almost every young adult and child with a smartphone does. ...

If you browse the web, I’m willing to bet you’ve encountered of an HTTP status code at some point in time. A dreadful 404 when the page is missing; 301/302 when you’re redirected to another page; or a good old 200 when you actually get to see the page. Well, I decided to do a translation of the meaning of some of most common HTTP codes into examples that non-techies can possibly relate to. Here we go! ...