Everybody can make DeepFakes without writing a single line of code.
Do you dance? Do you have a favourite dancer or performer that you want to see yourself copying their moves? Well, now you can!
Imagine having a full-body picture of yourself. Just a still image. Then all you need is a solo video of your favourite dancer performing some moves. Not that hard now that TikTok is taking over the world…
Image animation uses a video sequence to drive the motion of an object in a picture. In this story, we see how image animation technology is now ridiculously easy to use, and how you can animate almost anything you…
Literate programming is now a reality through nbdev and the new visual debugger for Jupyter.
Notebooks have always been a tool for incremental development of software ideas. Data scientists use Jupyter to journal their work, explore and experiment with novel algorithms, quickly sketch new approaches and immediately observe the outcomes.
However, when the time is ripe, software developers turn to classical IDEs (Integrated Development Environment), such as Visual Studio Code and Pycharm, to convert the ideas into libraries and frameworks. But is there a way to transform Jupyter into a full-fledged IDE, where raw concepts are translated into robust and reusable modules?
To this end, developers from several institutions, including QuantStack, Two Sigma, Bloomberg and…
Turn your Windows machine into a developer workstation with WSL 2.
I used to have an Apple laptop as my daily driver. I could do almost everything there; development, proposal writing, music composition etc. But the fear of vendor lock-in, the concern that I am depended on Apple’s whims and vices — which are arguably very expensive — led me to seek a new solution.
See Part II here:
I started building a machine learning workstation; a great CPU, lots of RAM and a competent GPU, among others. My OS of choice for almost anything was Ubuntu, except I needed Microsoft Office for proposal writing. Office online is just not there…
Delegate the challenging tasks to another player
Python is a fantastic programming language and the author’s language of choice. In my opinion, Python is the best language to learn as you are slowly breaking your way into the Computer Science and programming world.
However, every programming language has its strengths and weaknesses; this is why we have so many of them, after all. Different use cases call for different designs and implementations. As we say, there is no one size fits all solution.
Python is a user-friendly, easy to learn, free to use, portable, and easily extensible programming language. …
How to use the TFRecord format to train neural networks efficiently
TensorFlow is one of the most popular Deep Learning frameworks today. Some people swear by it, and some think it is a great but bloated tool, one that carries a heavy burden of legacy code.
Personally, I prefer working with PyTorch, but in my opinion, every Machine Learning (ML) researcher or engineer should know how to find their way into a TensorFlow repository. There is a lot of innovation in the field, and almost half of it is expressed using TensorFlow.
However, for the most part, TensorFlow is an opinionated framework. …
How to run AutoML experiments on Kubeflow with Kale and AutoSklearn
Given a task, a metric, a training dataset, as well as a resource budget, an AutoML system can automatically produce a set of predictions on a test dataset. The budget could refer to computational resources, such as CPU and/or wall clock time and memory usage.
The above paragraph is the definition of AutoML. To put it simply, when you launch an AutoML experiment, you provide the training dataset and the end goal you expect. The end goal, in plain English, could be something like this: Find me a model that, when you fit it on this training dataset it can…
Monitor and troubleshoot services in complex distributed systems, like Kubernetes.
Imagine you deploy an application that reports back the current prices of cryptocurrencies in USD. If you want to visualize it, think of something similar to CoinMarketCap.
Now, let’s assume that CoinMarketCap responds in under 3 seconds. That means that if users navigate to their page, they can get the price for the coin they are interested in quickly. On the other hand, your application needs at least 8 seconds to provide an answer. I bet that you won’t have a lot of users after one or two weeks!
You need to pinpoint the problem quickly. What is taking so…
Why is monitoring crucial for cloud-native applications and what tools do the job?
Imagine being imprisoned in a windowless cell with no calendar or wall clock. Moreover, you get to have no visitors, and your only company is a guard who does not like small talk. I know this is a very dark scene I am putting you in but bear with me.
You have one goal: find out the season (e.g., summer or autumn) and whether it is day or night outside. How could you do that? Well, you could observe the guard’s behavior, what he wears, what food he eats, is he tanned or not? If he is wearing sunglasses, then…
What are the alternatives to one of the most well-designed CLI tools out there?
I know that some of you reading these lines already hate me. Some of you could and actually spend every working hour in front of a terminal window; you love it. There is nothing wrong with it, and some Command Line Interface (CLI) tools are so well designed that even if you had a graphical user interface, you would most probably never use it.
I hear you! I actually love working inside a terminal window. I love the ViM editor, my workstation is an Ubuntu server virtual machine and I SSH into it every day, and until recently, I was…
Machine Learning engineers have their own design patterns as well!
Keras is a Machine Learning (ML) library built on top of TensorFlow, making it extremely easy to create and fit Deep Learning model architectures. As they like to say, “Keras API is designed for human beings, not machines.”
And that’s true! If you want to quickly sketch up an idea, Keras is the tool for the job. However, Keras can be very flexible and powerful; you can gradually peel the layers of complexity and dive deeper to customize almost every little detail.
Moreover, Keras can take advantage of multi-GPU configurations or TPU training because of its TensorFlow-backed backend.
In this…
