I remember when I started learning Python in my university days and found this “thing” called Anaconda.
To me, it was basically an all-in-one Python package that comes bundled with a lot of packages. Goodbye
pip install, I can finally focus on the code instead of managing the requirements.
The problem would come a while later when I was working on a task for my Machine Learning class.
It was a pretty straightforward task, load csv dataset, do feature engineering, create some visualisations, and then train a model.
“Nice, I should be able to sleep for 8 hours tonight,” I thought to myself. …
128 Petabytes. Not Terabytes, Petabytes. That’s how much storage space the Hadoop File System (HDFS) had when I first started working with big data.
We have all heard of the term big data, but I believe we never fully understand it before getting a hands-on experience.
I first learnt about it during my sophomore year in the university and even worked on “big data” in my first job.
I was responsible for setting up a pipeline to process 10 MB of generated data everyday. Which would amount to around 3.65 GB of data per year.
We even decided to not use Hadoop since the overhead of loading the data from HDFS is much longer than simply reading the data directly through the file system. …
Bzzz! My always-on-vibrate phone buzzes in my pocket as I walked along the Orchard Road in Singapore on a beautiful Saturday morning.
It buzzes a few more times in quick succession after the first one, but I thought nothing of it since I have tried to ignore messages on weekends.
I learned that disengaging from chats and social media will help you better appreciate your time with people around you.
Once I arrived back home, I was surprised to see it was from someone who had not messaged me for a very long time. I don’t really know this person, I have talked with him before, but not that much. …
Covid-19 has caused massive disruption to industries around the world. Airline and tourism were among the first ones to be hit hard due to entry restriction by most countries in an effort to curb the pandemic’s spread. Giant startups like Airbnb and Uber, among others, have also laid off some of their workers in an effort to shed expenses. Famous consulting firms, Accenture and Deloitte, did the same thing a couple of months ago. The list goes on and on.
Among these industries, there is one, in particular, that may usher in the next trend in machine learning and AI— the retail industry. …
Apple has always thrown a lot of big and powerful words around in their marketing. The following quote was taken from the latest Apple Event on October 13.
For example, Deep Fusion uses machine learning on the Neural Engine for pixel-by-pixel processing of photos with unprecedented detail, texture, and minimal noise. (source)
As far as I know, image processing will process images pixel-by-pixel, because that is the only way to do it. What other data would you use to process an image aside from the pixels?
I am not undermining Apple’s technology. With Ian Goodfellow himself as the Director of Machine Learning, it’s safe to bet that Apple plans to continue developing technologies based on Generative Adversarial Networks. …
Have you ever bought a mattress?
Let me tell you about my experience with the notorious mattress salesmen.
Salesmen would talk their way into making you buy something you don’t really need or a more expensive version of something you do need.
Personally, I like to shop in peace. That means I would prefer not having a salesman follow me while I browse. However, it is nearly impossible to find a mattress store without salesmen.
Once you heard one of the sales pitches, you realise that all of them are exactly the same. …
OpenAI’s GPT-3 had been in the spotlight for quite a while now. It is currently deemed as the state-of-the-art for NLP-related tasks, achieving better results than its predecessors.
GPT-3 is not yet publicly available. However, OpenAI have allowed access of the model’s API for beta testers, letting people experiment with the model.
As it turns out, the model can even create codes in various languages just by processing descriptions in natural language. Here is one of the examples posted in Twitter.
These kind of tweets about GPT-3’s capabilities have sparked a lot of reactions. An article titled “Will The Latest AI Kill Coding?” entertained the idea of AI taking over programming jobs, followed promptly by another article “GPT-3 Will Not Take Your Programming…
Airbnb is arguably the poster child of a successful platform business. In The Business of Platforms, the company is praised over and over throughout the book and for good reasons. They have global presence and a strong business model.
Having global presence means future competitors will have a hard time to establish their business in the same market. It is still possible, but it would require huge initial cost to overpower Airbnb and capture its existing market.
The business model is straightforward, hosts and users both get charged when they are doing a transaction. On the other hand, simply listing properties or browsing available ones are free of charge. Compared to Uber, where they subsidised every trips and even gave incentives to the drivers to stay in the company, Airbnb’s business model has bigger potential to be profitable. …
A while ago, I was browsing through arXiv’s recent paper submissions in Machine Learning when I came across an interesting title.
I decided to dive deeper into it, and found out that the authors successfully combine and use several machine learning models to create a framework called “Graph Network-based Simulators” (GNS).
As you can see on the image above, the predicted water particle movement managed to behave similarly with the ground truth. It also produced comparable result for different starting conditions and other particles such as goop and sand too.
Contrary to existing simulation that requires re-rendering for any change in starting conditions, this model only needs to be trained once and can successfully predict how the particles would behave in different conditions. …
Throughout my journey working with data, I have discovered a tool that will help save your time and make you more productive, no matter what programming language you are using.
When you run any program from the terminal, you are actually using shell to run it. Any command you type on the terminal, it runs on shell.
Unfortunately, most of us only learn a small amount of shell, mainly
ls to navigate through directories.
Other than that, maybe we learn tool-specific commands such as
docker , and language-specific commands to compile and run different programming languages. However, we often treat remembering these commands as part of learning a tool or programming language instead of learning the shell itself. …