Explainable Monitoring: Stop flying blind and monitor your AI

Data Science teams find Explainable Monitoring essential to manage their AI Photo by Bruce Warrington on Unsplash We’re living in unprecedented times wherein a matter of a few weeks, things changed dramatically for many humans and businesses across the globe. With COVID-19 spreading its wings across the globe and taking human lives we are seeing … Read more

Understanding Markov Decision Process: The Framework Behind Reinforcement Learning

Okay, Let’s get started. To get a better understanding of MDP, we need to learn about the components of MDP first. The future depends only on the present and not on the past. That statement summarises the principle of Markov Property. On the other hand, the term Markov Property refers to the memoryless property of … Read more

An Example of a Calibrated Model that is not Fully Calibrated

[This article was first published on R – Win Vector LLC, 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 our last note we mentioned the possibility of … Read more

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Microsoft Cloud for Healthcare: Unlocking the power of health data for better care

As healthcare providers have faced unprecedented workloads (individually and institutionally) around the world, the pandemic response continues to cause seismic shifts in how, where, and when care is provided. Longer-term, it has revealed the need for fundamental shifts across the care continuum. As a physician, I have seen first-hand the challenges of not having the … Read more

Register now! Brazilian Conference on Data Journalism and Digital Methods – Coda.Br 2020

[This article was first published on R Consortium, 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 November 2nd-7th, 2020, the 5th edition of the Brazilian Conference on … Read more

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Upcoming workshop: Think like a programmeR

[This article was first published on Mirai Solutions, 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. Learn how to program like a professional: boost your R skills and … Read more

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7 Rules for Writing an Elegant Program

Become a unique programmer Photo by Austin Distel on Unsplash First, programming is a language to communicate with a computer system. Communication is sharing thoughts with someone. Binary language is the native language of the computer system. But in the front end, we have lots of languages. Those languages use an interpreter to convert front … Read more

Active and Semi-Supervised machine learning: Oct 12–23

In the domain of computer vision, active learning approaches are most often evaluated on either image classification or object detection (meaning, we aim to either assign image-level class labels, or draw bounding boxes around objects and identify them). However, another common computer vision task, semantic segmentation, where class labels are assigned at the pixel level, … Read more

On gender bias in word embeddings

What analogies can tell us about our language and our algorithms The Natural Language Processing (NLP) group at Stanford University made publicly available the list of papers from their CS 384 seminar on Ethics and Social Issues in Natural Language Processing, and so I have been on a bit of a reading binge trying to … Read more

How to make your own Instagram filter with facial recognition from scratch using python

Image by teguhjati pras; Creative Commons License via Pixabay Over the past 10 years, Facial recognition technology has developed rapidly and has quickly developed a variety of uses. From the utilitarian (unlocking your phone), to playful (Instagram filters), to the controversial (security, surveillance, and policing), our faces can be used by tech in many ways. … Read more

ONNX: Preventing Framework Lock in

An introduction to the use of the ONNX standard for the interoperability between Deep Learning frameworks. Photo by Rick Mason on Unsplash In this blog, we are going to see what the ONNX standard is, its components and how to carry out interoperability between different Deep Learning frameworks. This blog will address the following sections: … Read more

Best Practices for Collaborative Data Science

Five ways to help ensure projects deliver real business value Photo by Myriam Jessier on Unsplash Given the diverse range of skill sets required, data science projects are perfect prototypes for collaborative technical work. However, collaboration, in general, has become much more difficult as the world navigates the global pandemic and most people continue to … Read more

String Matching With FuzzyWuzzy

This tutorial will go over how to match strings by their similarity. FuzzyWuzzy can save you ample amounts of time during the data science process by providing tools such as the Levenshtein distance calculation. Along with examples, I will also include some helpful tips to get the most out of FuzzyWuzzy. String matching can be … Read more

Organise your Jupyter Notebook with these tips

You may have heard of DRY principle: Don’t Repeat Yourself. If you haven’t heard of this software engineering principle before, it is about “not duplicating a piece of knowledge within a system”. One of my interpretation of this principle in Data Science is to create functions to abstract away the reoccurring tasks to reduce copy … Read more

Why R? Webinar – How to start your own rstats group – Building an inclusive and fun R community

[This article was first published on http://r-addict.com, 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 Thursday we have Kyla McConnell and Julia Muller from Freiburg R-Ladies with … Read more

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How to Use SQL in Pandas

Add another relational database skill into your data science toolkit https://images.unsplash.com/photo-1489875347897-49f64b51c1f8?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=800&q=60 If you consider the structure of a Pandas DataFrame and the structure of a table from a SQL Database, they are structured very similarly. They both consist of data points, or values, with every row having a unique index and each column having a … Read more

48 Hours to Results: The Story Behind California’s COVID-19 Model | Oct 2020

On March 16, 2020, four days before the stay-at-home decision was issued, all California had was an out-of-date internal forecast and limited, state-level-only projections from outside research labs. Our group initially consisted of representatives from the California State Government, along with a handful of Silicon Valley volunteer technologists. Luckily, one of the state epidemiologists had … Read more

The Double Density Plot Contains a Lot of Useful Information

[This article was first published on R – Win Vector LLC, 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. The double density plot contains a lot of useful … Read more

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Plot the Mandelbrot Set with Matplotlib

Source: https://unsplash.com/photos/rSrK-P0Wips If you, like me, think that fractals are beautiful, and have some knowledge of Python, you will enjoy this article. We will follow very easy steps to visualize the Mandelbrot Set using the library matplotlib. The Mandelbrot Set is formally defined as the set of complex numbers for which the function: Fc(Z) = … Read more

A CRAN Downloads Experiment

I’ve done an experiment regarding package downloads from CRAN (or the RStudio CRAN mirror at least) and now it’s time to share the results. library(dplyr) library(ggplot2) library(purrr) library(dlstats) library(flextable) flextable_style – function(x) { x %>% flextable() %>% bold(part = “header”) %>% # bold header bg(bg = “#D3D3D3”, part = “header”) %>% # puts gray background … Read more

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artificial EM

[This article was first published on R – Xi’an’s Og, 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 addressing an X validated question on the use of … Read more

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Big Data: Its Benefits, Challenges, and Future

Big Data is commonly associated with other buzzwords like Machine Learning, Data Science, AI, Deep Learning, etc. Since these fields require data, Big data will continue to play a huge role in improving the current models we have now and allow for advancements in research. Take Tesla, for example, each Tesla car that has self-driving … Read more

Stateful serverless on Google Cloud with Cloudstate and Akka ServerlessStateful serverless on Google Cloud with Cloudstate and Akka ServerlessDeveloper Advocate at Google CloudHead of Cloud Engineering and Deputy CTO at Lightbend

In recent years, stateless middle-tiers have been touted as a simple way to achieve horizontal scalability. But the rise of microservices has pushed the limits of the stateless architectural pattern, causing developers to look for alternatives. Stateless middle-tiers have been a preferred architectural pattern because they helped with horizontal scaling by alleviating the need for … Read more

How college students are handling COVID-19

Overall A sentiment analysis using VADER (Valence Aware Dictionary and sEntiment Reasoner) shows that, generally speaking, students posting on the UT Austin subreddit are feeling neutral. Although it would be easy to attribute this to college students feeling dead inside — especially at this point in the semester — the large percentage of neutral text … Read more

New digital course: Advanced Testing Practices using AWS DevOps Tools

The 2.5-hour course demonstrates how to incorporate testing and security into continuous integration, delivery, and deployment pipelines using AWS DevOps tools—including AWS CodePipeline and AWS CodeBuild. You’ll learn about advanced principles of DevOps methodology and the benefits of automating various types of testing (such as unit, integration, and security testing). The course also explains how … Read more

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Logistic Regression in Python

Import the libraries Load the data EDA Data Wrangling(Cleanse the data) Assign features to x and y Train and Test Calculate Accuracy Prediction 1.Import the libraries import numpy as npimport pandas as pdimport seaborn as snsimport matplotlib.pyplot as plt 2.Load the data Dataset — results.csv contains hours vs results. [Number of hours students studies vs … Read more

Analyzing how StyleGAN works: style incorporation in high-quality image generation

On the left, we have the generated image. In the middle, 4 different noises applied to a selected sub-region. The standard deviation of a big set of samples with different noise can be observed on the right. The awesomeness arises by the fact that they were also able to quantify the disentanglement of spaces for … Read more

Azure Cost Management and Billing updates – October 2020

Whether you’re a new student, thriving startup, or the largest enterprise, you have financial constraints, and you need to know what you’re spending, where, and how to plan for the future. Nobody wants a surprise when it comes to the bill, and this is where Azure Cost Management and Billing comes in. We’re always looking for … Read more

Migrate your Hadoop data lakes with WANDisco LiveData Platform for Azure

It’s no secret that organizations consider data as one of their most valuable assets and are investing to build their capability for data-driven decision making. It is challenging to manage a flexible and cost-effective data estate on-premises, and we are seeing customers embrace Azure for its best-in-class analytics solutions rapidly. However, migrating analytics workloads can … Read more

Economics for Tech People — Supply (Part 2)

Load Libraries To work through the project, we will need the readxl and tidyverse packages. If you do not have them installed in your R environment, simply remove the “#” sign before the “install.packages…” lines of code [1]. Once they are installed, you will not need to install them again on your machine. Here’s the … Read more

Analysis of Wave Power

Wave power analysis from data recorded on offshore buoys located in New Hampshire and Rhode Island. Image by author Although most people don’t think of locations like New Hampshire and Rhode Island as popular destinations for surfing, wave energy data obtained from the National Data Buoy Center shows that on occasion there is significant wave … Read more

Data Preparation Guide for detecting Histopathologic Cancer Detection

Machine learning models use data stored in the computer/server’s memory. Sometimes, the dataset is small enough to fit in the memory; but in most practical cases, it is not. To overcome this, we can use generators (they also perform image augmentation, but I manually performed that above instead) which take our images, and passes them … Read more

How to use Twitter’s API in R.

A quick guide to getting the Timeline and Retweeters of a User using R. Twitter has developed a streamlined and unique API for general public use. Although there are premium versions available, the majority of content for data analysis can be performed using the free accounts. Here, the steps of setting up a developer account … Read more

A false sense of security

Or why you should be wary when investment firms tell you they ran 1000 simulations So, a couple of days ago, I got into a little squabble with my dad about what to do with some cash that I had lying around in my bank. I wanted to invest the money to generate a better … Read more

94% Perfect: the Surprising Solution to the $200 Billion Inventory Problem

Many companies still use the traditional Target Stock Level (TSL) model to drive stock decisions. Which is a complex way of saying sell one get one — the literal meaning of the world Replenishment. And, the highly uncertain nature of demand requires inventory managers to operate on much higher safety stock margins than otherwise necessary. … Read more

The Central Limit Theorem (CLT): From Perfect Symmetry to the Normal Distribution

How can the Normal Distribution arise out of a completely symmetric set-up? The so-called Central Limit Theorem (CLT) is a fascinating example that demonstrates such behaviour. If you want to get some intuition on what lies at the core of many statistical tests, read on! The Central Limit Theorem (CLT) states: The sum (or the … Read more

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Reading and Manipulating Genomic Data in Python Photo by National Cancer Institute on Unsplash PySnpTools is a Python library of reading and manipulating genomic data in Python. It allows users to efficiently select and reorder individuals (rows) and SNP locations (columns). It then reads only the data selected. Originally developed to support FaST-LMM — a … Read more

10 Must-Know Tidyverse Functions: #1 – relocate()

[This article was first published on business-science.io, 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 article is part of a R-Tips Weekly, a weekly video tutorial that … Read more

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