3 Mistakes That Transformed My Machine Learning Career

Part of Embracing Mistakes Involves Sharing Them Photo by krakenimages on Unsplash Let’s face it, we all make mistakes. Mistakes can sometimes be costly but in them lie our greatest life lessons, and oftentimes, a major opportunity for growth. We humans, naturally try to avoid making mistakes, since for so long, mistakes have been associated … Read more

How to Analyze Continuous Data from Two Groups

Traditional statistics are not understood by most data science practitioners. Many modern figures are not utilized by traditional statisticians. Let’s bridge this gap. Imagine a task. You have tens or hundreds of features available to predict an outcome. Let’s say this outcome is the number of clicks on an eCommerce web page. Let’s say you … Read more

Amazon AppStream 2.0 is now available in the AWS Europe (London) region

You can now deploy Amazon AppStream 2.0 in the AWS Europe (London) Region. Deploying AppStream 2.0 in your local region provides users with a more responsive experience and helps support your local data residency obligations. With this launch, you can deploy General Purpose, Compute Optimized, Memory Optimized, Graphics Design, Graphics Pro and Graphics G4 instances … Read more

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Dashboard using Streamlit with data from SQL database

An interactive dashboard from customer and sales data Image by Author Introduction Streamlit is one of the most recent python libraries for powerful dashboard creation and an open source framework for machine learning and data science teams. It can produce industry standard and visually attractive dashboards with very simple coding. I have created a sales … Read more

What to Expect When You Are Expecting the Delta Covid-19 Variant

[This article was first published on Fells Stats, 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. SARS-Cov-2 (COVID-19) has been the defining driver of the market since its … Read more

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Reinforcement Learning vs Bayesian Optimization: when to use what

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 should not rely on an author’s works without seeking professional advice. See our Reader Terms for details. Optimization is the key of most of the Machine … Read more

Build a platform with KRM: Part 4 – Administering a multi-cluster environmentBuild a platform with KRM: Part 4 – Administering a multi-cluster environmentDeveloper Programs Engineer

This is part 4 in a multi-part series about the Kubernetes Resource Model. See parts 1, 2, and 3 to learn more.  Kubernetes clusters can scale. Open-source Kubernetes supports up to 5,000 Nodes, and GKE supports up to 15,000 Nodes. But scaling out a single cluster can only get you so far: if your cluster’s … Read more

Code performance in R: Parallelization

[This article was first published on INWT-Blog-RBloggers, 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 is the third part of our series about code performance in R. … Read more

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Speeding Up R Shiny – The Definitive Guide

Better App Performance – It Can Be Done! Prototyping apps in Shiny is fast and easy, but once an app grows, performance issues may arise. Speeding up Shiny is possible and the methods described below can prevent or resolve these issues. There are a few good practices to have in mind in order to keep … Read more

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6 Research Papers about Machine Learning Deployment Phase

For my studies, I’ve curated 6 research papers I will be reading to learn more about machine learning deployments going forward. Here are the research papers in non-chronological order: 1. Challenges in Deploying Machine Learning: A Survey of Case Studies, Paleyes et al, Jan 2021 Machine learning practitioners and researchers face a number of challenges … Read more

China’s AI ambitions and why they matter

Jeffrey Ding on China’s big AI push APPLE | GOOGLE | SPOTIFY | OTHERS Editor’s note: This episode is part of our podcast series on emerging problems in data science and machine learning, hosted by Jeremie Harris. Apart from hosting the podcast, Jeremie helps run a data science mentorship startup called SharpestMinds. There are a … Read more

Unit 3) Genetic Algorithms (Part 2) Advanced Topics

Evolutionary Computation Course Advanced Topics in Genetic Algorithms — Control Parameters, Selective Mating, and GA Variants Hello and Welcome back to this full course on Evolutionary Computation! In this post we will cover Unit 3 (Part 1) of the course, Genetic Algorithms — Advanced Topics. In the previous post we implemented a simple but yet … Read more

GitHub Copilot. A Rise and Fall Story for the Software Engineering Industry

GitHub and OpenAI have announced Copilot, an AI assistant that can assist coders by generating or autocompleting code for their software solutions. What does this mean for the software engineering industry? “Programming Code Macro” by qubodup is licensed under CC BY 2.0 It was mid June 2021 when Sam Altman, OpenAI’s CEO, published a tweet … Read more

Intraclass Correlation Coefficient in R-Quick Guide

[This article was first published on Methods – finnstats, 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. Intraclass Correlation Coefficient in R, ICC is used to determine if … Read more

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Advancing safe deployment with AIOps—introducing Gandalf

“Changes to Azure services and the Azure platform itself are both inevitable and beneficial, to ensure continuous delivery of updates, new features, and security enhancements. However, change is also a primary cause of service regressions that can contribute towards reliability issues—for hyperscale cloud providers, indeed for any IT service provider. As such, it is critical … Read more

Euro 2020: Will Switzerland kick out Spain too?

One of the big sensations of the UEFA Euro 2020 is that Switzerland kicked out world champion France. We take this as an opportunity to share with you a simple statistical model to predict football (soccer) results with R, so read on! Football is a highly stochastic game, which is one of the reasons for … Read more

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Create a custom metric with tidymodels and NYC Airbnb prices

[This article was first published on rstats | Julia Silge, 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 is the latest in my series of screencasts demonstrating … Read more

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Draw me a project

I’ll be giving a remote keynote talk at the Rencontres R (French R conference) on July the 12th, all in French. This blog post is a written version of my presentation, but in English. I decided to not talk about package development for once, but rather about workflows and how to structure & run an … Read more

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Tired: PCA + kmeans, Wired: UMAP + GMM

[This article was first published on r on Tony ElHabr, 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. Introduction Combining principal component analysis (PCA) and kmeans clustering seems … Read more

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Reasons to Use Tidymodels

I was listening to episode 135 of ‘Not so standard deviations’ – Moderate confidence The hosts, Hilary and Roger talked about when to use tidymodels packages and when not. Here are my 2 cents for when I think it makes sense to use these packages and when not: When not you are always using GLM … Read more

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Concentration Inequalities in Machine Learning

[This article was first published on YoungStatS, 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 fifth “One World webinar” organized by YoungStatS will take place on September … Read more

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7 Famous AI Quotes Explained

“The development of full artificial intelligence could spell the end of the human race. […] It would take off on its own, and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.” — Stephen Hawking Stephen Hawking, a renowned physicist, warned us of the … Read more

My Best Way to Learn a New Data Science Tool

The comparison also makes it easier to get familiar with the syntax. Although different software tools are likely to have different syntax, the structure of the syntax for common operations follow a similar pattern. Let’s do a slightly more complicated example. This time we will add another tool which is the data table package of … Read more

The Elevator Optimization Problem.

Photo by Izhak Agency on Unsplash Recently, I completed a small project that required me to make suggestions for optimizing an elevator configuration within a theoretical high-rise in New York City. The building is set up as follows. Entrants to the building must first swipe badges through a security system, then they can push the … Read more

Evolutionary Computation (FULL COURSE) Overview

https://unsplash.com/photos/FHnnjk1Yj7Y Evolutionary Computation Course Introductory post about the material, concepts, and applications I will be covering throughout this brand new series! Hello Everyone! I’ve decided to create an entire course over Evolutionary Computation. In this post I will give only a brief overview of the course! Evolutionary Computation is a sub-field of Computational Intelligence, a … Read more

Text analysis in the social sciences

A new spectrum of possibilities Computer scientists have long profited from methodology that allows them to extract information from a variety of text documents. Their methodology not only tallies up terms and phrases in texts, but it also uncovers structure and provides insight into the content of texts. On the other hand, most social scientists … Read more

AWS Lambda now supports SASL/PLAIN authentication for functions triggered from self-managed Apache Kafka

AWS Lambda functions that are triggered from self-managed Apache Kafka topics can now access usernames and passwords secured by AWS Secrets Manager using SASL/PLAIN, a simple username/password authentication mechanism that is typically used with TLS for encryption to implement secure authentication. This is in addition to SASL/SCRAM, which is already supported on Lambda. To get started, customers … Read more

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Use Vertex Pipelines to build an AutoML classification end-to-end workflowUse Vertex Pipelines to build an AutoML classification end-to-end workflowStaff Developer Advocate

The example notebook has the full component definition. Sharing component specifications When the component is compiled, we can also request that a yaml component specification be generated. We did this via the optional output_component_file=”tables_eval_component.yaml” arg passed to the @component decorator. The yaml format allows the component specification to be put under version control and shared … Read more

Calibrating an Agent-Based Model of Cell Replication

Explaining partial synchronicity in real-world cell samples Agent-based models provide an alternative way of exploring and explaining the world. They can provide predictive and explanatory power through the logic that informs their behavior, especially if they are calibrated to real-world data. In this paper, researchers constructed a mathematical model to predict the partial synchronicity that … Read more

Canonical Correlation Analysis

In this article, you will learn everything you need to know about Canonical Correlation Analysis. Canonical Correlation Analysis is a Multivariate Statistics technique that allows you to analyze correlations between two datasets. Canonical Correlation Analysis can be used to model the correlations between two datasets in two ways: Focusing on a dependence relationship, and model … Read more

Speeding Up Data Visualization

Using Klib for Data Visualization in a Single Line of Code Source: By Author Data visualization helps us in understanding data and finding out different patterns, associations, and visual insights. There are a large variety of visualizations that can be used according to the problem that we are trying to solve. Python provides N number … Read more

Genetic Algorithms for Natural Language Processing

Why GA’s are effective for preprocessing NLP data Figure 1: genetic algorithm training a red square to avoid blue rectangles. Image by author. “Data preparation accounts for about 80% of the work of data scientists.“ — Forbes NLP modeling projects are no different — often the most time-consuming step is wrangling data and then developing … Read more

SOLID Coding in Python

We can solve this by turning all the functions we wrote into subclasses of a class. In this case, I have created an abstract class called “Operations” with an abstract method “get_operation”. (Abstract classes are generally an advanced topic. If you don’t know what an abstract class is, you can run the following code even … Read more

Transition plot in R-change in time visualization

[This article was first published on Methods – finnstats, 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. Transition Plot in R, when we have quantitative data for change … Read more

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Get the Odds of Euro 2020 Games based on FIFA World Ranking

[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. We will provide an example of how you can estimate … Read more

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Euro 2020 Predictive Model based on FIFA Ranking System

[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. In a previous post, we built a Predictive Model based … Read more

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Bring cloud experiences to data workloads anywhere with Azure SQL enabled by Azure Arc

From edge to cloud, companies are eager to find innovative solutions that meet them where they are. Today’s business environment is increasingly complex, and customers tell us they need solutions that are multi-cloud, platform-agnostic, and offer integrated apps and services that are always up to date. We’ve seen firsthand the best solution combines a company’s … Read more

Gentle Introduction to Forecasting with Modeltime [Video Tutorial]

[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. A gentle introduction to our forecasting package, modeltime. Modeltime extends the Tidymodels ecosystem … Read more

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Ace Your Computer Vision Job Interview

Let’s get started with our first, and most important tip: make sure you understand the job. You need to know the organization, their funding, the team structure, culture, your potential teammates, and prepare to prove you have the skills needed to do the job. Computer vision requires basic skills, usually acquired by working with these … Read more