2021-04 Luminance Masks in R Graphics

[This article was first published on R – Stat Tech, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. This document describes an extension of the support for masks … Read more

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Abstracting Data Loading with Airflow DAG Factories

Creating an abstraction layer for improved scalability and usability for loading Google Sheets data with Airflow This topic is not new. I’ve seen quite a few articles about generating different levels of abstractions for Airflow DAGs. For example, this article explains how to generate DAGs programmatically, and this library allows you to generate DAGs using … Read more

What Do 101 Dalmations and Machine Learning Have in Common?

There are at least 101 Examples of Machine Learning Data Scientists can use to Create Valuable Insights. Here they are. Junior — a very good boi, Courtesy of Jim Ozminkowski Recently I was asked to help prepare an organization for an expected increase in business requiring artificial intelligence. AI for that firm would focus on … Read more

Data Science in Marketing: A Beginner’s Guide

Marketing Analytics with Python — Datacamp If you have already taken a beginner level data science course and have a basic understanding of machine learning models, you can consider taking this Datacamp track. It consists of 7 courses, and takes you through concepts like analyzing marketing campaigns with Python, sentiment analysis, customer churn prediction, market … Read more

Gold-Mining Week 13 (2021)

[This article was first published on R – Fantasy Football Analytics, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Favorite

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Pivoting ML Apps to Success

3 lean validations to make sure you’re on the right path Photo by Pixabay from Pexels One of the main differences between AI and general developments is the required evaluation scope. On regular apps by knowing what to do and how, validating the need and keeping it simple, you’re almost safe. But on AI apps … Read more

Announcing preview of AWS Private 5G

Today, we are announcing the preview of AWS Private 5G, a new managed service that helps enterprises set up and scale private 5G mobile networks in their facilities in days instead of months. With just a few clicks in the AWS console, customers specify where they want to build a mobile network and the network capacity … Read more

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Bazaarvoice uses Recommendations AI to improve CTR by 60%Bazaarvoice uses Recommendations AI to improve CTR by 60%Customer Engineer, Google Cloud

Not long ago, building AI into recommendation engines was a daunting, expensive task that could take years to get off the ground. But as Bazaarvoice has shown, with the help of cloud services, the time from AI investment to business outcomes is shorter than ever.  Bazaarvoice is the leading provider of product reviews and user-generated … Read more

Introducing the Machine Learning Reproducibility Scale

Quantifying machine learning reproducibility and presenting a unified ranking system for project reproducibility The reproducibility of machine learning projects is a recurring topic, brought up in many different contexts — both in academia and industry. There are a lot of opinions, mainly focused on tooling, which is great but can lead to a focus on … Read more

AutoXGB for Financial Fraud Detection

In line with the recent rise of AutoML solutions, AutoXGB is a library that automatically trains, evaluates, and deploys XGBoost models from tabular data in CSV format. The hyperparameter tuning is done automatically using Optuna, and the deployment is carried out with FastAPI. AutoXGB was developed by Abhishek Thakur, a researcher at HuggingFace who holds … Read more

R shiny web apps at scale on AWS with ShinyProxy

[This article was first published on R – YakData, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. Related Favorite

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Over-squashing, Bottlenecks, and Graph Ricci curvature

The majority of Graph Neural Network (GNN) architectures are based on the message-passing paradigm, in which information is propagated between the nodes of the graph along its edges. Traditionally, the input graph is used both as part of the data (along with the node features) as well as the computational structure for information propagation. Recent … Read more

Run Pandas as Fast as Spark

Why the Pandas API on Spark is a total game changer Photo by Clayton Holmes on Unsplash That’s it. It’s out. Spark now has a Pandas API. It seems that, every time you want to work with Dataframes, you have to open a messy drawer where you keep all the tools, and carefully look for … Read more

Tracking Aerosol Pollution from Space

Time series extraction of aerosol pollution of a region using Google Earth Engine Photo by Call Me Fred on Unsplash Smoggy weather can be frequently observed in many parts of the world nowadays. Fine solid particles suspended in the air play a major role in causing smoggy conditions by absorbing or scattering sunlight. These particles … Read more

Introducing Azure Load Testing: Optimize app performance at scale

Today, we are announcing the preview of Azure Load Testing. Azure Load Testing is a fully managed Azure service that enables developers and testers to generate high-scale load with custom Apache JMeter scripts and gain actionable insights to catch and fix performance bottlenecks at scale. Application performance and resiliency are more important than ever before. … Read more

On the impossibility of explaining AI

…and its consequences. Shadows (image by the author). You are at the office of some physician waiting for them to describe what course of treatment they are going to recommend for your problem. It is not a life-threatening problem, but it is one that has had a serious impact on your life. It has made … Read more

A Hiring Manager’s review of the Google Data Analytics Professional Certificate syllabus

30 November 2021 “Is the Google Data Analytics Professional Certificate any good?” Whether you’re a job seeker looking to boost your career or a hiring manager eager to find skilled staff, this is a pertinent question. In this review, I assess the certificate based on the syllabus, and not the course content itself i.e. I … Read more

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Create Analysis-Ready Datasets from the U.S. Bureau of Labor Statistics Flat-Files Web

A step-by-step guide The U.S. Bureau of Labor Statistics (BLS) website is one of the rich sources of U.S. economic data frequently visited by research economists, data scientists, finance professionals, journalists, and data enthusiasts in search of information about the economy. The website regularly publishes data about employment, unemployment, inflation and prices, productivity, consumer spending, … Read more

Hello! I am PAMI

A new Pattern Mining Python library for Data Science Figure 1: Broad classification of learning algorithms across Artificial Intelligence, Data Mining, Machine Learning, and Deep Learning Big Data Analytics represents the set of techniques to discover knowledge hidden in large databases. These techniques can be broadly classified into four types: Pattern mining — aims to … Read more

rOpenSci News Digest, November 2021

Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog. Now let’s dive into the activity at and around rOpenSci! rOpenSci HQ Community call: @ropensci-review-bot help! Tuesday, 07 December 2021 17:00 UTC we’ll share how we are Enhancing Software Peer Review with GitHub Automation. Speakers Arfon Smith, … Read more

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Explainable AI: An illuminator in the field of black-box machine learning

SHAP (Shapley Additive Explanations): Shapley Additive Explanations or SHAP is based on the concept of Shapley values from game theory. The main idea behind SHAP is to know how much each individual feature contributes to make a certain prediction. This might be tricky to calculate the individual contribution as there may exist interaction among features. … Read more

Have You Ever Heard of NVidia’s AI GauGAN2?

Here you can see some different moods for the same drawing and input: Different moods of GauGAN2. source: Own image. Different lighting, bright blue. Source: Own image. Icy and Glaciers, GauGAN2 creation. Source: Own image. What model is behind the AI GauGAN2? As I shortly mentioned before, GauGAN2 is based on Generative Adversarial Networks. Of … Read more

4 Ways Your Startup Can Use AI Right Now (Without Breaking The Bank)

You don’t need big budgets, data scientists, or even months of effort – 4 ways your startup can become AI-driven today Artificial intelligence (AI) is what computer scientist Andrew Ng calls “the new electricity.” However, despite its abilities and appeal, AI is not a fit for every situation. In my earlier article, I presented 5 … Read more

Developing the Go Game (围棋) using matplotlib and NumPy — Part 1

Drawing the Go Board using matplotlib Source: https://en.wikipedia.org/wiki/Go_(game)#/media/File:FloorGoban.JPG Most aspiring data scientists are no strangers to matplotlib — the data visualization library that was designed for creating static, animated, and interactive visualizations in Python. And most of the time your experience in using matplotlib might be using it to plot charts, as such bar charts, … Read more

Layer conductance from scratch

Implementation NB: We will use the same model and data from the first part of this series. To compute layer conductance we adopt the same strategy as for Integrated Gradients — because the model is saturated, to see meaningful gradients we need to capture them from baseline to input. Below we are computing the conductance … Read more

Building a Chess Engine: Part 2

Learning chess by combining AlphaGo and Transformers Hi everyone, this will be the second instalment in my tutorial series for building a chess engine. This lesson will focus on building an AI agent that we can play. This lesson is going to be more technical than part 1, so please bear with me. I try … Read more

7 Techniques to Handle Multicollinearity that Every Data Scientist Should Know

Essential guide to detect and handle multicollinearity in the dataset Image by Gerd Altmann from Pixabay Exploratory data analysis and statistical analysis are important components of a data science model development pipeline to generate insights about the data. Before fitting a machine learning model, a data scientist needs to perform various feature engineering and data … Read more

Want to supercharge your DevOps practice? Research says try SREWant to supercharge your DevOps practice? Research says try SREDeveloper Relations Engineer

How Google achieves reliability: SRE In Google’s early days, we took a traditional approach to technical operations; the bulk of the work involved manual interventions in reaction to discrete problems. However, as our products began to rapidly acquire users across the globe, we realized that this approach wasn’t sustainable. It couldn’t scale to match the … Read more

Introducing Amazon EC2 M6a instances

Amazon Web Services (AWS) announces the general availability of general purpose Amazon EC2 M6a instances. M6a instances are powered by 3rd generation AMD EPYC (code named Milan) processors with an all-core turbo frequency of 3.6 GHz, deliver up to 35% better price performance compared to M5a instances, and 10% lower cost than comparable x86-based EC2 … Read more

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Why R? 2021 agenda is almost there!

[This article was first published on Why R? Foundation, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. We are 2 weeks before the fifth edition of Why R? … Read more

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Understand Q-Q plot using simple python

An effective way to visualize data Image by Author Introduction Engineers and scientists work with data. Without data, they are not able to draw any conclusion. Now is the era of creation of data everyday from every aspects of our lives. Some data are random and some are biased. Some may suffer from bias because … Read more

Three Steps to Better A/B Tests

A simple guide to improving testing at your organisation Photo by National Cancer Institute on Unsplash A/B tests originate from the land of academia and science, where they are known by their much fancier name, Randomised Control Trials. They have been used by organisations in every sector to improve things for their users and in … Read more

EARL 2021 charity donation

After another fantastic EARL Conference held online this September, we are delighted to share that we were able to donate £8,000 to DataKind UK. The aim of the Enterprise Applications of the R Langauge Conference is to inform, educate and inspire, and we certainly feel inspired by the great work DataKind UK have done this … Read more

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SONiC opens more opportunities for network innovation

SONiC, as an open-source operating system for network devices, has been growing rapidly in the last five years. According to Gartner Market Guide for Data Center Switching published early this year, they predict, “By 2025, 40 percent of organizations that operate large datacenter networks (more than 200 switches) will run SONiC in production environments.” And, … Read more

October 2021: “Top 40” New CRAN Packages

[This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don’t. One hundred forty-one new packages made it to CRAN in October. Here … Read more

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