A Simple Post-Processing Step to Improve the Fairness of Collaborative Recommender Systems
Author(s): ___ Originally published on Towards AI. Overview In this article, I will describe an algorithm that can be applied as a post-processing step to alleviate the popularity bias inherent in collaborative filtering-based recommender systems. The content of this article is based …
A Decision Support System for Disaster Risk Management in Madagascar
Author(s): Tadeusz Bara-Slupski Originally published on Towards AI. Addressing natural disaster risk as a data science consultancy One of the challenges posed by climate change is the increased risk of catastrophic natural events. These are likely to disproportionately affect most vulnerable areas …
Geolocation Data Analysis of Lagos.
Author(s): Lawrence Alaso Krukrubo Originally published on Towards AI. Using EDA and Machine Learning to find prime office locations in Lagos The problem weβre going to solve using Geolocation data analysis and Machine Learning, is helping a new Tech Start-Up find the …
Emoticon and Emoji in Text Mining
Author(s): Dhilip Subramanian Originally published on Towards AI. Converting Emoticon and Emoji into word form using Python Source: wallpaperplay In todayβs online communication, emojis and emoticons are becoming the primary language that allows us to communicate with anyone globally when you need …
The Too-small World of Artificial Intelligence
Author(s): Sergii Shelpuk Originally published on Towards AI. Overcrowded and overlooked parts of the AI world I spent the last eight years as an insider of the artificial intelligence (AI) community, working for different companies and in various roles. At DeepTrait, with …
A Gentle Introduction to Graph Embeddings
Author(s): Edward Ma Originally published on Towards AI. TransE Top highlight Photo by Edward Ma on Unsplash Instead of using traditional machine learning classification tasks, we can consider using graph neural network (GNN) to perform node classification problems. By providing an explicit …
Autonomization: The Future of Jobs
Author(s): Heidar (Amir) Pirzadeh Originally published on Towards AI. Yeah, yet another article on the future of jobs! I mean itβs always safe and easy: if someone predicts this type of thing correctly they will be remembered and they can brag about …
How To Use Counterfactual Evaluation To Estimate Online AB Test Results
Author(s): ___ Originally published on Towards AI. Definition In this article, I will explain a principled approach to estimate the expected performance of a model in an online AB test using only offline data. This is very useful to help decide which …
Random Walk in Node Embeddings (DeepWalk, node2vec, LINE, and GraphSAGE)
Author(s): Edward Ma Originally published on Towards AI. Graph Embeddings Top highlight Photo by Steven Wei on Unsplash Instead of using traditional machine learning classification tasks, we can consider using graph neural network (GNN) to perform node classification problems. By providing an …
A Practical Tip When Working With Random Samples On Spark
Author(s): ___ Originally published on Towards AI. In this article, I will share a crucial tip when using Spark to analyze a random sample of a data frame. The code to reproduce the results can be found here. Itβs an HTML version …
When Variance and Standard Deviation Fail to Explain Variability!
Author(s): Astha Puri Originally published on Towards AI. We all know the definition of variance β it helps us understand how dispersed the data points are, around the mean. If the data points are far off from the mean, we have larger …
Top Restaurant Finder Nearby
Author(s): Chittal Patel Originally published on Towards AI. Photo by Jay Wennington on Unsplash Introduction In this project, I created a Basic Data Science Project namely Top Restaurant Finder which will give the top Restaurants near your address. I did explore the …
Generate Quotes with Web Scrapping, Glove Embeddings, and LSTM in Pytorch
Author(s): Lakshmi Narayana Santha Originally published on Towards AI. Introduction With the rise of advancement in research in NLP specially in Language Models, text generation – a classical machine learning task which solved using Recurrent Networks. In this article we walk through …