It goes without saying that choosing an evaluation set is the most important step in any machine learning process. This becomes even more crucial when it comes to active learning since this will be our measure of how well our model performance improves during our iterative labelling process. Furthermore, it also helps us decide when … Read more How to do more with less data ?— Active learning

If you’re reading this, then you’re most likely going through the grind of preparing for technical interviews (software engineers, data scientists, etc). By now you should know that tech interviews are not like regular ‘old school’ interviews — we can’t just woo the hiring manager with our charm and talk out of our ass — … Read more Become an Expert at the Technical Interview — Part I

Especially for recent graduates aspiring to become the next tech superstars Courtesy of Janko Ferlič from Unsplash It is well know that Leaders are Readers, and this does hold true in the tech industry just like it does anywhere else. However, this article is not about preaching to you about the necessity of reading for … Read more 3 Books for Successful Programmers in 2020 and beyond

As the ultimate store of value, gold has appreciated substantially over the past 18 months; rallying from ~$1,300 in March 2019 to $1,954 on September 18 th; an increase of 33.4%. In fact, gold as an asset class has performed very well over the past 20 years and has markedly outperformed stocks; though this has … Read more Drivers of Gold Returns in R

The directory .github\workflows, when pushed to GitHub, will be read by GitHub and used as the GitHub Actions folder — where we store YAML files for our workflows! But what is a YAML file? Well, according to our beloved Wikipedia — “YAML is a human-readable data-serialization language. It is commonly used for configuration files and … Read more Deploy Angular Apps to Firebase From GitHub

ML in RPA 1) can be easy, 2) it requires a different mindset and 3) it has numerous use cases In the Posti project, a software robot used machine learning to fill the purchase invoice process forms. Photo by Mantas Hesthaven on Unsplash The RPA team of Posti, the Finnish logistics giant, started to use … Read more Top 3 Insights from using Query-based ML to Automate Invoice Processing

We also participate in the FanTeam version of the FPL, where we had our best performing team of the week. Again, not the best captain choice — Leicester scored 4 goals and Vardy was somehow not involved even in one of them. So, I’d say our luck was quite poor last week overall, but somehow … Read more EPL Fantasy GW2 Recap and GW3 Algo Picks

Modularity and code readability A Dash app can be conceptualized as being made of three main blocks of code. The first of these is the application layout, which contains the structure of the web page, including all the interactive widgets and core components (dropdowns, text inputs, etc.) required by the user to modify an app’s … Read more An extensible, interactive visualization framework to measure gender bias in the news

The eponymous PageRank algorithm, which is under the hood of the famed Google search, is surprisingly simple in its bare bones avatar. Most algorithms, when they are made to work in practice, undergo a zillion minor changes to be effective and efficient, these modifications to PageRank are out of the current scope of this article. … Read more Exploring the Indian Premier League using PageRank

Evaluating how recommender systems learn about users by comparing Instagram to TikTok Image by Trist’n Joseph “Based on your activity, we think that you might like this.” That phrase is one of the most common phrases seen on almost every social media platform, and there is a good reason for it. The conversion rate on … Read more Based on your activity, you should like this: Instagram vs TikTok!

Rewriting the rules in GAN: Copy & paste features contextually Editing StyleGAN model to add a helmet to the horse [Source] GAN architecture has been the standard for generating content through AI, but can it actually invent new content outside what’s available in the training dataset? Or it’s just imitating the training data and mixing … Read more Generating Novel Content without Dataset

Orange is an open-source tool that allows us to perform a wide range of data-manipulation tasks such as data visualization, exploration, preprocessing and modeling creation without the need to use Python, R or any other piece of code. It’s ideal if you’re taking your first steps in this long learning-path. It’s also suitable for more … Read more Is it Possible to Make Machine Learning Algorithms without Coding?

Photo by Jess Bailey on Unsplash [12]. So there you go, these were 10 essential Jupyter Notebook extensions for Data Scientists or anyone else who likes to code and develop in a Jupyter Notebook as well. I hope you learned some new tricks that can make your job as a Data Scientist easier. Keep in … Read more 10 Essential Jupyter Notebook Extensions for Data Scientists

Functional testing has many categories, and you can use different ones based on your goals of performing the testing process. To better discuss the difference between the various functional testing categories, let’s discuss the 5 most used functional testing techniques. №1: Unit testing Unit testing is usually performed by the developer writing different unit tests … Read more A Brief Introduction to Software Testing

Content based recommender is a recommendation model that returns a list of items based on a specific item. A nice example of this recommenders are Netflix, YouTube, Disney+ and more. For example, Netflix recommends similar shows that you watched before and liked more. With this project, you will have a better understanding of how these … Read more Building a Movie Recommender using Python

#1 — Hidden Technical Debt in Machine Learning Systems 🙈 The team at Google Research provides clear instructions on antipatterns to avoid when setting up your data science workflow. This paper borrows the metaphor of technical debt from software engineering and applies it to data science. via DataBricks As the next paper explores in greater … Read more 5 Must-Read Data Science Papers (and How to Use Them)

Production logging approaches for AI and data pipelines By Isaac Backus and Bernease Herman Photo by Petri R on Unsplash It’s 2020 and most of us still don’t know when, where, why, or how our models go wrong in production. While we all know that “what can go wrong, will go wrong,” or that “the … Read more Profile and log your ML data | by Isaac Backus

Gadfly.jl on the surface follows the simple methodology that most Julia users are familiar with. We can create a simple plot using the plot() method, with two key-word arguments, X and Y. using Gadflydata = Dict([:X => [5,10,32,31,51,43], :Y => [82, 33, 21, 26, 11, 22]])plot(x=data[:X], y=data[:Y]) (Image by author) Here is where things get … Read more Gadfly.jl — The Pure Julia Plotting Library From Your Dreams

How to understand whether an ML model is really doing what you want it to Photo by Feliphe Schiarolli on Unsplash When the hard work of building a model is done, someone has to make the final decision of whether to press “go” and release the model into the wild. This is the crucial moment … Read more Evaluating Machine Learning Models

The worst thing that can happen to your AI endeavor, is that you end up damaging people’s lives through good intentions. Photo by lauren lulu taylor on Unsplash The worst thing that can happen to your AI endeavor, is that you end up damaging people’s lives through good intentions. Without proper AI ethics practices, your … Read more Trust: Why AI Ethics and MLOps go hand-in-hand

Anomaly detection is a critical problem that has been researched within diverse research areas and application disciplines. This article aims to construct a structured and comprehensive overview of the selected algorithms for anomaly detection by targeting data scientists, data analysts, and machine learning specialists as an audience. Concept of Anomaly Detection An unexpected change that … Read more Outlier or Inlier: Types of Algorithms to Detect Anomalous Behavior

An investigation into the role of idioms in sentiment analysis Note: The methodology behind the approach discussed in this post stems from my PhD thesis and can be found in this academic paper. Sentiment analysis (or opinion mining) aims to automatically extract and classify sentiments (the subjective part of an opinion) and/or emotions (the projections … Read more ️ Sentiment Analysis: Idioms and their Importance