Strengthen zero trust access with the Google Cloud CA serviceStrengthen zero trust access with the Google Cloud CA serviceProduct ManagerHead of Solutions Strategy

At launch, we showed how CAS allows DevOps security officers to focus on running the environment and offload time consuming and expensive infrastructure setup to the cloud. Moreover, as remote work continues to grow, it’s bringing a rapid increase in zero trust network access (example), and the need to issue an increasing number of certificates … Read more

Using Docopt in python, the most user-friendly command-line parsing library

Now that we have created our file, we can create a file as long as a requirements.txt file to make our project even more user-friendly. A file is a python file where you describe your module distribution to the Distutils, so that the various commands that operate on your modules do the … Read more

3 Basic Steps of Stock Market Analysis in Python

Analyze Tesla stock in Python, calculate Trading Indicators and plot the OHLC chart. Includes a Jupyter Notebook with code examples. Photo by Chris Liverani on Unsplash Note from Towards Data Science’s editors: While we allow independent authors to publish articles in accordance with our rules and guidelines, we do not endorse each author’s contribution. You … Read more

Attributes in R

In R, objects are allowed to have attributes, which is a way for users to tag additional information to an R object. There are a few reasons why one might want to use attributes. One reason that I encountered recently was to ensure that the type of object returned from a function remains consistent across … Read more

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Solving IoT device security at scale through standards

Edge Compute Node protection profile (ECN PP)—now available—guides you to engineer, claim, evaluate, and consume device security for IoT. Internet of Things (IoT) solution builders these days are more likely to deploy IoT solutions with unsecured devices because they cannot verify device security claims from device makers. Solution builders could create secured devices themselves, however … Read more

Deep Learning based Recommender Systems

A gentle introduction to modern movie recommenders Traditionally, recommender systems are based on methods such as clustering, nearest neighbor and matrix factorization. However, in recent years, deep learning has yielded tremendous success across multiple domains, from image recognition to natural language processing. Recommender systems have also benefited from deep learning’s success. In fact, today’s state-of-the-art … Read more

Three Ways to Create Dockernized LaTeX Environment

Getting Started with LeTeX + Docker + VSCode Remote Container Photo by Arisa Chattasa on Unsplash IntroductionSetupMethod 1: tianon/latexMethod 2: Remote-ContainersMethod 3: Creating your containerHow to switch Remote containersOpening a PDFConclusionReferences We can run a Docker application in any environment, Linux, Windows, or Mac. Docker provides a set of official base images for most used … Read more

Anchors Away! Regex in R | by Drew Seewald

Tutorial | R | Regular Expressions (Regex) Secrets to working with text using advanced regular expressions tools in R Photo by Peter Hansen on Unsplash So you already know the basics of regular expressions, or regex, in R. Things like how to use character sets, meta characters, quantifiers, and capture groups. These are the basic … Read more

How AI Techniques Made Me a Better Parent for Our Toddler

I used the knowledge and wisdom I gained from my work in Artificial Intelligence to understand and teach my two-year-old son more effectively and regain my sanity. Image via Unsplash and Freepik Overview The knowledge I have gained from building Artificial Intelligence (AI) tech is directly applicable to raising my toddler. Not only does it … Read more

Build a Shiny Dashboard with Elasticsearch

5. Connect to Elasticsearch elasticsearch <- import(“elasticsearch”)host <- “localhost:9200″es <- elasticsearch$Elasticsearch(hosts = host) There are various way for the connection since AWS4Auth is not used. You may use a R only approach as well. 6. Install the necessary packages for the Shiny dashboard including Shiny, shinyWidgets and shinydashboard. Manipulate Data and Build Shiny Dashboard using … Read more

How to Clean Text Files at the Command Line

A basic tutorial about cleaning data using command-line tools: tr, grep, sort, uniq, sort, awk, sed, and csvlook Photo by JESHOOTS.COM on Unsplash Cleaning data is like cleaning the walls in your house, you clear any scribble, remove the dust, and filter out what is unnecessary that makes your walls ugly and get rid of … Read more

What To Do When You Can’t AB Test

Image by the author Will the new search software improve sales conversion? What’s the incremental impact of our new store pickup process on omni-channel sales? Can you find out today? I’m a data scientist at Best Buy Canada and these are some of the important questions we work to answer to support product development and … Read more

What can AI learn from the Brain?

What Is Intelligence? When we think about intelligence in the military sense of the word, we think about knowledge. Other might add skills to the definition of intelligence. And yet others would claim intelligence is ability to acquire and apply that knowledge and those skills. I think the best definition of intelligence I’ve seen is … Read more

Dealing with Imbalanced dataset

Techniques to handle imbalanced data Image from Fidel Fernando, from Unsplash The imbalanced dataset in real-world problems is not so rare. In layman terms, an imbalanced dataset is a dataset where classes are distributed unequally. An imbalanced data can create problems in the classification task. Before delving into the handling of imbalanced data, we should … Read more

Silhouette Method — Better than Elbow Method to find Optimal Clusters

Deep dive analysis of Silhouette Method to find optimal clusters in k-Means clustering Image by Mediamodifier from Pixabay Hyperparameters are model configurations properties that define the model and remain constants during the training of the model. The design of the model can be changed by tuning the hyperparameters. For K-Means clustering there are 3 main … Read more

Video + code from workshop on Deep Learning with Keras and TensorFlow

[This article was first published on Shirin’s playgRound, 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. Workshop material Because this year’s UseR 2020 couldn’t happen as an in-person … Read more

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Personal Art Map with R

[This article was first published on R on , 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. Map art makes beautiful posters. You can find them all over … Read more

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All About ‘Time’ In PySpark

Feature Engineering Using PySpark Concept, Format, and Conversion of Time Data with PySpark Code Example Photo by Ales Krivec on Unsplash When we travel to a foreign country, the different time systems can be a headache issue. Sometimes, after several hours of flight, we might arrive in a foreign country with local time even earlier … Read more

Bayesian Modelling of UK Stop and Search

There are significant difficulties with measuring disproportionate use of stop and search due to the difficulties in controlling for potentially varying crime participation and availability. This project accounts for these by looking at stop and search in proportion to arrests, acting as a minimum threshold for disproportionality. Aggregating stop and search and arrests at the … Read more

Why developers love TypeScript every bit as much as Python

And why you might consider switching if you’re dealing with front-end web, or back-end Node development Python and TypeScript are among the most-loved programming languages. Photo by Obi Onyeador on Unsplash Python is my bread-and-butter, and I love it. Even though I’ve got some points of criticism against the language, I strongly recommend it for … Read more

How much faster is image integral?

Compare brute force to image integral using Google Colab In my quest to learn more about computer vision and python, I’ve been reading about the Viola-James object detection frame work, best summarized by the paper here. In it, they describe the concept of an image integral, a sort of summed area table for an array … Read more

The First Programming Design Pattern in pxWorks

[This article was first published on gtdir, 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. First of all, we need to explain a few things in more detail. … Read more

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Video: How to Scale Shiny Dashboards

This presentation was a part of a joint virtual webinar with Appsilon and RStudio entitled “Enabling Remote Data Science Teams”. Find a direct link to the presentation here.  How to Scale a Shiny App to Hundreds of Users In this video, Appsilon’s VP of the Board & Co-Founder Damian Rodziewicz explains best practices for scaling … Read more

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Calculus of Variations Demystified

Before finding the shortest path, we need to be able to calculate the length of a path from A to B. As the famous Chinese proverb say, “a journey of a thousand miles begins with a single step”. So, let’s calculate the length of a small passage and integrate it from A to B. Image … Read more

Tableau Desktop Specialist Certification (Tips & Guide)

Earlier this month, I passed my Tableau Desktop Specialist exam. I would like to share my pleasant experience for everyone’s benefit. Also, I discovered that students are entitled to great bonuses! I divide my sharing into 5 segments: What and Why Preparations Exam Format Exam experience Result & Tips! Photo by Carlos Muza on Unsplash … Read more

Hack: The ‘[‘ in R lists

[This article was first published on R – Predictive Hacks, 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. Assume that you have a list and you want to … Read more

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BASIC XAI with DALEX— Part 1: Introduction

BASIC XAI Introduction to model exploration with code examples for R and Python By Anna Kozak Hello! Welcome to “BASIC XAI with DALEX” series. In this post, we will take a closer look at some algorithms used in explainable artificial intelligence. You will find here an introduction to methods of global and local model evaluation. Each description will … Read more

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Hack: The “count(case when … else … end)” in dplyr

[This article was first published on R – Predictive Hacks, 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. When I run quires in SQL (or even HiveQL, Spark … Read more

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Manage Your Entire R Code Base With TODOr

Search Scope TODOr can look at more than just a project, you can also have it search a single file: todor::todor_file(“my_file.Rmd”) Or even an entire R package: todor::todor_package() Markers By default, TODOr will look for all of the aforementioned comment markers. You will get a list of all of them returned to you but what … Read more

Deploying a Simple UI for Python

Streamlit recently introduced the Streamlit Sharing service to facilitate deployment of Streamlit projects. Using the service requires a few quick steps. 1. Create a requirements.txt You can create this using the following command while in your project’s environment: pip freeze > requirements.txt 2. Push your project to GitHub Create a public repository for your project … Read more

What I learnt from giving 120+ Data Science Presentations

In 1869, French civil engineer Charles Minard visualised the movement of Napoleon’s Russian campaign in 1812. Whilst it is difficult to construct such charts even now, it is a stunningly simple chart that articulates six variables in one 2D plot! (temperature, troop count, travelled distance, direction of travel, lat/long and location relative to specific dates). … Read more

Hidden Markov Model (HMM) — simple explanation in high level

HMM answers these questions: Evaluation — how much likely is that something observable will happen? In other words, what is probability of observation sequence? Forward algorithm Backward algorithm … Decoding — what is the reason for observation that happened? In other words, what is most probable hidden states sequence when you have observation sequence? Viterbi … Read more

Predicting Housing Prices with R

Load Libraries The first task is to load up a few libraries that we will need to complete the project. For this, all we need are the forecast, tseries, and tidyverse libraries. Click the name in the previous sentence for links to the documentation for each! Here’s the code: # If these libraries are not … Read more

How to Auto-Update PDF When Working on Latex

Guide to Auto-Update PDF Using latexmk and VSCode Photo created by creativeart — IntroductionInstalling LaTeXCreating PDF from a terminal using latexmkInstalling LaTeX Workshop Extension to VS CodeCreate your own snippetsTesting the snippetLaTeX Workshop errorAutomatically update PDF when you saveConclusionReference I am an occasional LaTeX user. I use Typora for writing articles, reports, notes, and … Read more

Is there enough space in Manhattan to stay six feet apart? | by András Hann

I am a big fan of reproducible research. Therefore, I wrote the analysis in an iPython notebook that you can find here. It has everything in it from downloading the data to calculating statistics and drawing maps. For those familiar with geographical analysis in Python, it won’t be surprising that my main tools were the … Read more

Data to Text generation with T5; Building a simple yet advanced NLG model

An implementation of Data-to-Text NLG model by fine-tuning T5 Image by author The Data to text generation capability of NLG models is something that I have been exploring since the inception of sequence to sequence models in the field of NLP. The earlier attempts to tackle this problem were not showing any promising results. The … Read more

How to create a concise image representation using machine learning

Designing and training an autoencoder on HRRR images in Keras Autoencoder examples on the internet seem to be either about toy examples (MNIST, 28×28 images) or take advantage of transfer learning from ImageNet bottleneck layers. I will show you how to train an autoencoder from scratch, something that you will do if you have enough … Read more

Classifying images with torch

[This article was first published on RStudio AI Blog, 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. In recent posts, we’ve been exploring essential torch functionality: tensors, the … Read more

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Multiple Gauge Plots with Facet Wrap

[This article was first published on exploRations in R, 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. Intro Here are some good examples of how to generate gauge … Read more

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