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Data Science

Can you use Machine Learning to predict which tweets will go viral?

Photo by Alexander Shatov on Unsplash

In a previous article, I wrote about building an XGBoost model to predict video popularity for a past data science competition. It covered everything from loading the data and libraries to building the model itself.

Bitgrit has recently released a new competition with $3000 💵 up for grabs:


Data Scientists, Analysts, Data Engineers, and Machine Learning Engineers. What do they do?

Photo by Alex Kotliarskyi on Unsplash

According to World Economic Forum, High Scalability, by 2025, the amount of data generated each day is expected to reach 463 exabytes globally. That’s a billion gigabytes!. Google, Facebook, Microsoft, and Amazon store at least 1,200 petabytes of information.

To utilize this eruption of data, data professions have become ubiquitous…

Artificial Intelligence

The privacy upgrade for Machine Learning

For many Machine Learning applications, tons of data is needed for it to work. The problem, however, is user data is sensitive and private.

Rising concerns of privacy and the call for data rights pose an issue for the traditional way of training and developing machine learning models, which require…

Computer Vision

A look at Nexus and Portal, a no-code MLOps platform that allows you to train, test and deploy state-of-the-art cv models

Photo by Farhan Azam on Unsplash

Are you a Computer Vision enthusiast interested in training Computer Vision models, but limitations of your local machine or spending hours writing tons of code is stopping you?

Or are you an ML practitioner looking to streamline your ML stack instead of wrangling with cv2 or matplotlib codes just to…

Interpretable ML

Methods to interpret any Machine Learning model

Photo by Emily Morter on Unsplash

The real world is complex, with a flood of variables interacting with each other. This is why most machine learning models applied in the real world are made up of complex architectures compared to a simple model like linear regression.

Most of the time, more complex models depending on the…

Artificial Intelligence

A quick look at how AI is applied in the real world today

Photo by Sean Pollock on Unsplash

In this era where vast amounts of data are generated every second, data is a valuable resource for businesses worldwide, which is why some call data the new oil.

To capitalize on data and derive value from it, Artificial Intelligence is needed, which is why it’s booming in the business…

Natural Language Processing

Building a text summarizer with Newspaper3k, Hugging Face, and Gradio

Photo by Obi Onyeador on Unsplash

Have a ton of articles bookmarked to read later but never got to them? Don’t have the time to read long articles?

Don’t you wish you could summarize them all and get the gist of the articles?

With Hugging Face 🤗 , you can!

In this article, I will be…

Data Science

A quick guide to sentiment analysis with NLTK on the subreddit r/technews.

Photo by Brett Jordan on Unsplash

Sentiment Analysis is the process of determining whether a piece of text is considered to be positive, negative, or neutral.

It’s an application of Natural Language Processing that has tons of use cases.

As stated in Wikipedia:

Sentiment analysis is widely applied to voice of the customer materials such as…

Data and AI

A curated list of reputable newsletters with quality content on DS, DE, ML, and AI.

Photo by Solen Feyissa on Unsplash

There’s an ocean of noise on the internet for data science and AI that it can be overwhelming to focus on good quality news and content.

As Herbert A. Simon says:

“…a wealth of information creates a poverty of attention…”

The solution to information overload?


If you’re someone who…

Benedict Neo

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