An introduction on working with image, audio, and text data
TensorFlow’s custom data format TFRecord is really useful. The files are supported natively by the blazing fast tf.data API, support distributed datasets, leverage parallel I/O. But they are somewhat overwhelming at first. This post serves as a practical introduction.
Overview
We will first go over the concept behind TFRecord files. With…
Getting Started
Might have a minimal bias towards Deep Learning
Have you ever asked yourself where you currently are on your Machine Learning journey? And what’s there that you can still learn about?
This checklist helps you answer such questions. It provides an outline of the field, divided into three broad levels: Entry level (where everybody starts), intermediate level (where…
Examine the effect of augmentations in your browser
When working with image data, practitioners often use augmentations. Augmentations are techniques that artificially and randomly alter the data to increase diversity. Applying such transformations to the training data makes the model more robust. For image data, frequently used candidates are rotating, resizing, or blurring. The effects of the transformations…
Getting Started
A guide to the evolution of generative networks
Introduction
In short, the core idea behind generative networks is capturing the underlying distribution of the data. This distribution can not be observed directly, but has to be approximately inferred from the training data. Over the years, many techniques have emerged that aim to generate data similar to the input samples.
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Be prepared to learn when using them for Machine Learning
The specs are indeed intimidating: Up to 32 GPU cores and up to 16 CPU cores. Pair that with 64 GB of RAM, and you’re well equipped for any workload. And, not to forget the design. Well, it seems Apple did it again.
But, did they really? Let’s dig a…
Add two lines of code to enhance your script
Most of the time, we write and debug our code locally. After we’ve passed any tests, we then deploy the scripts to a remote environment. If we’re fortunate, we might have access to multiple GPUs. …
How to handle all the parameters
Motivation
The common approaches to handling user-specific settings include parsing command line arguments or using separate python files that store definitions. For small projects, these techniques are easy to incorporate and maintain.
However, once you have to handle a plethora of configurable (hyper-)parameters, you’ll quickly lose track of the situation.
As…
Thoughts and Theory
Capturing the essential ingredients that make RL successful
The ability to make machines learn is a fascinating achievement of the last decades. Many new business opportunities have opened up, and companies use Machine Learning on a day-to-day basis.
It was only a couple of years ago that DeepMind’s AlphaGo algorithm beat Go world champion Lee Sedol. This spectacular…
Can free societies really appreciate their freedom?
As the moderator introduces the speaker, I look at the audience. I recognize some politicians from several neighbouring countries, artists, and other known people. How did I even get here? It was by pure happenchance, an old friend had tickets but was prevented from going. So she asked me if…
Steps you can use to pass, too
After preparing for a long time, I recently took and passed the TensorFlow Developer Certificate exam. This exam tests your proficiency in using TensorFlow for image, time-series, and text data. Beyond these domains, it also covers strategies to reduce overfitting, such as augmentations and dropout layers.
Why should you get certified?
There are two reasons…
