Just Keep Stacking — Implement Stacking Regression in Python using mlxtend

For the purpose of this post, I won’t discuss the preprocessing steps, but please refer to the Kaggle kernel for full detail. On a high level, I examined the distribution of each feature, removed outliers, create dummy variables for the categorical ‘room_type’ (since there are only three categories), and standardize the features. Train/Test Split I … Read more

Baby Weight Shiny app

[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. Alright, this is it: I am officially back! 😀 I have not … Read more

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COVID-19s Impact on the NYC Subway System

[This article was first published on R | JLaw’s R 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. At 8pm on March 22nd, 2020, the “New York … Read more

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Superdense Encoding of Classical Data

Using Dimensionality Reduction with Double Amplitude Encoding My immediately-previous article titled, “130,780-point Quantum Classification,” the circuit of which used 20 qubits to map all that data, resulted in a Twitter thread that inspired me to think about by how much I could reduce that qubit count. It honestly hadn’t been much of a thought with … Read more

Structural equation model trees with partykit and lavaan

[This article was first published on Achim Zeileis, 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. To capture heterogeneity in structural equation models (SEMs), the model-based recursive partitioning … Read more

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Remake Our Self

Thanks to Silicon Valley, software engineering is one of the most (excessively) glorified lines of work in the 21st century. More and more people every day are curious about entering software from other fields. I started programming in April, 2016. I began my software internship in April 2020. In July, 2020, I officially became a … Read more

Using Data Science to Make Your Next Trip on Boston Airbnb

Boston is the capital and the most populous city in the State of Massachusetts in the United States. Its economy, culture, history, and education attract hundreds-thousands of tourists each year. I have been eager to travel to this beautiful city so long and eventually make my plan this March. However, an unexpected global pandemic locks … Read more

Covid19: Correlation Between Confirmed Cases and Deaths

[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. What is the daily correlation of Confirmed versus Death Cases … Read more

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Using Scikit-learn’s Binary Trees to Efficiently Find Latitude and Longitude Neighbors

Bridging together sets of GPS coordinates without breaking your Python interpreter Image by Mohamed Hassan from Pixabay Engineering features from latitude and longitude data can seem like a messy task that may tempt novices into creating their own apply function (or even worse: an enormous for loop). However, these types of brute force approaches are … Read more

Analyzing Sonic Fan Art with data science

A tutorial on using BeautifulSoup to scrape DeviantArt The Sonic fandom has achieved a level of notoriety that few fandoms on the Internet enjoy. The art is known for being distorted, disturbing and in many cases, explicit. In my latest Youtube video, I scraped DeviantArt to analyze fan art to determine whether or not it … Read more

What is Linear Regression?

In this article, you will learn — What is a Linear Regression? How does it find the relation between input features and targets? How does it predict? How to evaluate the predictions? How to implement it in code? It tries to find out the best possible linear relationship between the input features and the target … Read more

Kaggle 3rd Place Solution — Jigsaw Multilingual Toxic Comment Classification

Approach, Learnings, and Code I had recently participated in the Jigsaw Multilingual Toxic Comment Classification challenge at Kaggle and our team (ACE team) secured 3rd place on the final leader board. In this blog, I describe the problem statement, our approach, and the learnings we had from the competition. I have also provided the link … Read more

Building a Face Recognizer in Python

We have long lines of code in this step. If you go through it you can easily understand what is happening in each line. Let’s define the variables that will be needed. face_locations = []face_encodings = []face_names = []process_this_frame = True Here comes the face recognition code. (You may need to reformat the spacing if … Read more

How To Build A Real-time Data Pipeline For An Online Store Using Apache Beam, Pub/Sub, and SQL

Step 3: Create Apache Beam Pipeline And Run It On Dataflow At this stage, we are getting the data in real-time from our virtual online store to our Pub/Sub subscriber. Now we are going to write our pipeline in Apache Beam to unnest the data and convert it into row like format to store it … Read more

How to build KNN from scratch in Python

k-Nearest Neighbors (KNN) is a supervised machine learning algorithm that can be used for either regression or classification tasks. KNN is non-parametric, which means that the algorithm does not make assumptions about the underlying distributions of the data. This is in contrast to a technique like linear regression, which is parametric, and requires us to … Read more

Tell me a joke— How to add Small Talk support to your Power Virtual Agents Chatbot.

SOLUTIONS FOR MICROSOFT POWER PLATFORM Small Talk is an essential feature of every Chatbot. With the help of QnA Maker and Power Automate, we add this capability to any Chatbot build with Microsoft’s Power Virtual Agents Photo by Jason Leung on Unsplash Whatever your Chatbot is designed for, and no matter how clear or simple … Read more

15 Tips and Tricks for Jupyter Notebook that will ease your Coding Experience

Optimize your work in Jupyter Notebook using these hacks Image by wiredsmartio from Pixabay Jupyter Notebook is a browser bases REPL (read eval print loop) built on IPython and other open-source libraries, it allows us to run interactive python code on the browser. It not only runs python code but also has many interesting plugins … Read more

Task 2 – Retail Strategy and Analytics

Hey Everyone! I’m back with anoher tutorial on the Task 2 of thsame virtual experience program.I completed this Virtual Experience Program a month back and I have posted the solutions of Task 1. You should visit that too before continuing this tutorial. This post is specifically about Task 2 – Experimentation and uplift testingYou can … Read more

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Column Names as Contracts

Software products use a range of strategies to make promises or contracts with their users. Mature code packages and APIs document expected inputs and outputs, check adherence with unit tests, and transparently report code coverage. Programs with graphical user interfaces form such contracts by labeling and illustrating interactive components to explain their intent (for example, … Read more

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How To Set Up Your System for Object Detection Models

There are two ways of building an object detection model. You can implement an existing model architecture. It takes a lesser amount of time and you get guidance from other implementations. Also, you can benefit from the method called transfer learning, which uses weights from previously built models and re-train the model for the current … Read more

ggwebthemes: Some ggplot2 Themes Optimized for Blogs

[This article was first published on Data Enthusiast’s 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. About ggwebthemes Not long ago, I published a post “Three ggplot2 … Read more

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End-to-end OptimalFlow Automated Machine Learning Tutorial with Real Projects — Formula E Laps…

Get the public timing and weather data from https://results.fiaformula.com, and keep their hierarchy, saving them in similarly structured folders. We will extract their folder dictionary as the features about Series Season(i.e. 2017–2018), Match Location(i.e. Berlin), Match Type(i.e. FP1), etc. Before you feed data to OptimalFlow modules, essential data engineering steps are required. There are 3 … Read more

Grassroots or Influencer Driven? A Social Network Analysis of the QAnon Conspiracy Theory

By Aadit Barua & Josh Barua Is QAnon a grassroots phenomenon, or is it largely driven by a few influencers? To be considered an influencer, a user must get a lot of attention from others in a network, which can be measured in Twitterverse as the share of retweets, replies and mentions a user receives. … Read more

Create a line graph with ggplot

[This article was first published on Quantargo 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. Use the geom_line() aesthetic to draw line graphs and customize its styling … Read more

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Two Tools Every Data Scientist Should Use For Their Next ML Project

Uber’s Manifold Photo by Dan Gold on Unsplash For my project, I am creating an Ensemble. An Ensemble is a collection of machine learning algorithms that each individually train and predict on the same data. The advantage of an Ensemble is that it provides a range of different strategies for finding a solution and utilizes … Read more

Calculating Vector P-Norms — Linear Algebra for Data Science -IV

Mathematical principles that underpin the regularization methods in Machine Learning In the Linear Algebra Series, to give you a quick recap, we’ve learned what are vectors, matrices & tensors, how to calculate dot product to solve systems of linear equations, and what are identity and inverse matrices. Continuing the series, the next very important topic … Read more

Don’t know the breed of your dog? ML can help!

Now we will see how using pre-trained features can make a huge difference. Download the ResNet-50 bottleneck features. You can extract the respective train, test and validation sets by running the code cell below: We will define the model again now and use GlobalAveragePooling2D on the extracted features which average an array of features into … Read more

Function Definition in Python

In computer programming, a function is a named section of a code that performs a specific task. This typically involves taking some input, manipulating the input and returning an output. In this post, we will go over how to define python functions, how to specify functions that can take an arbitrary number of positional arguments … Read more

Data Visualization: How to choose the right chart (Part 1)

We use a relationship method to display a connection or correlation between two or more variables. When assessing a relationship between data sets, we are trying to understand how two or more data sets combine and interact with each other. This relationship is called correlation, and it can be positive or negative, meaning that the … Read more

Top 10 Learning Resources for Graph Neural Networks

This book is a game changer and is currently available as pre-publication that can be downloaded online. It starts with beginners topics such as graph theory and traditional graph approaches to more advanced topics such as novel GNN models and state-of-the-art GNN research. It is a well designed and self-contained material that has most of … Read more

AWS Launch Wizard now supports SAP deployments with SUSE Linux Enterprise Server 15 SP1 and 12 SP5

AWS Launch Wizard offers a guided way of sizing, configuring, and deploying AWS resources for SAP HANA and SAP HANA-based Netweaver systems with a purpose built, easy to use wizard. The following table shows all of the operating systems currently supported for different SAP components that can be deployed with AWS Launch Wizard: AWS Launch … Read more

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Visualize How a Neural Network Works from Scratch

You can better understand how a simple neural network works by visualizing the results at each step Neural Network is often considered a black-box algorithm. Data visualization can help us better understand the principles of this algorithm. Since standard packages don’t give all details of how the parameters are found, we will code a neural … Read more

Meetings readiness checker APIs help developers ensure that end-users can join Amazon Chime SDK meetings from their devices

From the Amazon Chime SDK for JavaScript, a developer can call any of the nine meeting readiness checker methods. These consist of local tests for devices setup and network tests that confirm the application can connect to Amazon Chime by briefly joining and leaving a test Amazon Chime SDK meeting. When executing network tests, the … Read more

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Amazon Lightsail now offers new OS blueprints

In addition to providing compute instances preinstalled with your favorite OS, Lightsail bundles include storage and a generous amount of data transfer, so you have everything you need to get up and running, all for a fixed monthly price. After your bundles are deployed, Lightsail’s intuitive management console makes it easy to track metrics, create … Read more

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How to build a recommendation system in a graph database using a latent factor model

In-database training avoids exporting the data from the DBMS to other machine learning platforms thus better support continuous model updates A recommendation system is any rating system which predicts an individual’s preferred choices, based on available data. Recommendation systems are utilized in a variety of services, such as video streaming, online shopping, and social media. … Read more

Building a COVID-19 Map using ELK

Probably most of you are familiar with Johns Hopkins University (JHU) map representing the current situation of the COVID-19 pandemic. Image of the Johns Hopkins University (JHU) map (Johns Hopkins University) This map has been developed using ArcGIS technology, that has come the facto standard for developing pandemic maps in a lot of cases like … Read more

6 Best Startup Choices with Artificial Intelligence

Do you love text, lots of reading, pre-processing, and building models with text-based data? Bingo! This is the best choice to plan and build your startup on. The possibilities you have with natural language processing as a startup choice are diverse. These range from classification of text, segregation of useful data, construction of high-level chatbots, … Read more

Gotta go fast with “{tidytable}”

I’m back in business! After almost 5 months of hiatus, during which I was very busy with my new job, andnew house, I’m in a position where I can write again. To celebrate my comeback, I’ll introduce toyou the {tidytable} package, which I learned about this week on Twitter. {tidytable} is a package that allows … Read more

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Data Science Conference Austria 2020

[This article was first published on Quantargo 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. Data Science Conference Austria 2020 Data Science Conference (DSC) Austria is knocking … Read more

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A Shiny app on Hong Kong District Councillors

👀 TL;DR We built an R Shiny app to improve access to information on Hong Kong’s local politicians. This is so that voters can make more informed choices. The app shows basic information on each politician, alongside a live feed of their Facebook page and illustrative maps of their district. We took advantage of this … Read more

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