Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R...
Data science jobs continue to grow in 2019, and this report shares the change and spread of jobs by software over recent years.
View ArticleTen random useful things in R that you might not know about
Because the R ecosystem is so rich and constantly growing, people can often miss out on knowing about something that can really help them in a task that they have to complete
View ArticleHow to Make Stunning 3D Plots for Better Storytelling
3D Plots built in the right way for the right purpose are always stunning. In this article, we’ll see how to make stunning 3D plots with R using ggplot2 and rayshader.
View ArticleThe Evolution of a ggplot
A step-by-step tutorial showing how to turn a default ggplot into an appealing and easily understandable data visualization in R.
View ArticleKaggle Kernels Guide for Beginners: A Step by Step Tutorial
This is an attempt to hold the hands of a complete beginner and walk them through the world of Kaggle Kernels — for them to get started.
View ArticleTen more random useful things in R you may not know about
I had a feeling that R has developed as a language to such a degree that many of us are using it now in completely different ways. This means that there are likely to be numerous tricks, packages,...
View ArticleCoding Random Forests® in 100 lines of code*
There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least...
View ArticleR Users’ Salaries from the 2019 Stackoverflow Survey
Let’s take a look on what R users are saying about their salaries. Note that the following results could be biased because of unrepresentative and in some cases small samples.
View ArticleScikit-Learn vs mlr for Machine Learning
How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a...
View ArticleCustomer Segmentation for R Users
This article shows you how to separate your customers into distinct groups based on their purchase behavior. For the R enthusiasts out there, I demonstrated what you can do with r/stats, ggradar,...
View ArticleOrchestrating Dynamic Reports in Python and R with Rmd Files
Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and...
View ArticleHow to Visualize Data in Python (and R)
Producing accessible data visualizations is a key data science skill. The following guidelines will help you create the best representations of your data using R and Python's Pandas library.
View ArticlePlotnine: Python Alternative to ggplot2
Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to...
View ArticleBeginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero
This post presents a pipeline of building a KNN model in R with various measurement metrics.
View ArticleClassify A Rare Event Using 5 Machine Learning Algorithms
Which algorithm works best for unbalanced data? Are there any tradeoffs?
View ArticleServerless Machine Learning with R on Cloud Run
Expedite the deployment of your machine models using serverless cloud infrastructure. In this tutorial, we explore creating and deploying a model which scraps real time Twitter data and returns...
View ArticleBasics of Audio File Processing in R
This post provides basic information on audio processing using R as the programming language. It also walks through and understands some basics of sound and digital audio.
View ArticleIntroduction to Geographical Time Series Prediction with Crime Data in R,...
When reviewing geographical data, it can be difficult to prepare the data for an analysis. This article helps by covering importing data into a SQL Server database; cleansing and grouping data into a...
View ArticleGetting Started with R Programming
An end to end Data Analysis using R, the second most requested programming language in Data Science.
View ArticlePython and R Courses for Data Science
Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
View ArticleDecision Boundary for a Series of Machine Learning Models
I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the...
View ArticleTime Series Classification Synthetic vs Real Financial Time Series
This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.
View ArticlePython for data analysis… is it really that simple?!?
The article addresses a simple data analytics problem, comparing a Python and Pandas solution to an R solution (using plyr, dplyr, and data.table), as well as kdb+ and BigQuery solutions. Performance...
View ArticlemodelStudio and The Grammar of Interactive Explanatory Model Analysis
modelStudio is an R package that automates the exploration of ML models and allows for interactive examination. It works in a model agnostic fashion, therefore is compatible with most of the ML...
View ArticleBuild a Branded Web Based GIS Application Using R, Leaflet and Flexdashboard
By using R, Flexdashboard and Leaflet, we can build a customized and branded web application to showcase location based data interactively across the organization. Instead of crowding the application...
View ArticleData Science Tools Popularity, animated
Watch the evolution of the top 10 most popular data science tools based on KDnuggets software polls from 2000 to 2019.
View ArticlePractical Markov Chain Monte Carlo
This is a slightly more intricate example of MCMC, compared to many with a fairly simple model, a single predictor (maybe two), and not much else, which highlights a couple of issues and tricks worth...
View ArticleAn Introduction to Statistical Learning: The Free eBook
This week's free eBook is a classic of data science, An Introduction to Statistical Learning, with Applications in R. If interested in picking up elementary statistical learning concepts, and learning...
View ArticleUnderstanding Time Series with R
Analyzing time series is such a useful resource for essentially any business, data scientists entering the field should bring with them a solid foundation in the technique. Here, we decompose the...
View ArticleWrapping Machine Learning Techniques Within AI-JACK Library in R
The article shows an approach to solving problem of selecting best technique in machine learning. This can be done in R using just one library called AI-JACK and the article shows how to use this tool.
View ArticleData Science Tools Illustrated Study Guides
These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of...
View ArticleText Mining with R: The Free eBook
This freely-available book will show you how to perform text analytics in R, using packages from the tidyverse.
View ArticleBehavior Analysis with Machine Learning and R: The free eBook
Check out this new free ebook to learn how to leverage the power of machine learning to analyze behavioral patterns from sensor data and electronic records using R.
View ArticleTop 6 Data Science Programs for Beginners
Udacity has the best industry-leading programs in data science. Here are the top six data science courses for beginners to help you get started.
View ArticleSimple & Intuitive Ensemble Learning in R
Read about metaEnsembleR, an R package for heterogeneous ensemble meta-learning (classification and regression) that is fully-automated.
View ArticleR or Python? Why Not Both?
Do you use both R and Python, either in different projects or in the same? Check out prython, an IDE designed to handle your needs.
View ArticleUndersampling Will Change the Base Rates of Your Model’s Predictions
In classification problems, the proportion of cases in each class largely determines the base rate of the predictions produced by the model. Therefore if you use sampling techniques that change this...
View Article15 Free Data Science, Machine Learning & Statistics eBooks for 2021
We present a curated list of 15 free eBooks compiled in a single location to close out the year.
View ArticleCreating Good Meaningful Plots: Some Principles
Hera are some thought starters to help you create meaningful plots.
View ArticleSupport Vector Machine for Hand Written Alphabet Recognition in R
We attempt to break down a problem of hand written alphabet image recognition into a simple process rather than using heavy packages. This is an attempt to create the data and then build a model using...
View ArticleData Science Curriculum for Professionals
If you are looking to expand or transition your current professional career that is buried in spreadsheet analysis into one powered by data science, then you are in for an exciting but complex journey...
View ArticleThe Most In-Demand Skills for Data Scientists in 2021
If you are preparing to make a career as a Data Scientist or are looking for opportunities to skill-up in your current role, this analysis of in-demand skills for 2021, based on over 15,000 Data...
View Article5 Tips for Writing Clean R Code
This article summarizes the most common mistakes to avoid and outline best practices to follow in programming in general. Follow these tips to speed up the code review iteration process and be a...
View ArticleIntroduction to Statistical Learning Second Edition
The second edition of the classic "An Introduction to Statistical Learning, with Applications in R" was published very recently, and is now freely-available via PDF on the book's website.
View Articleebook: Learn Data Science with R – free download
Check out this new book for data science beginners with many practical examples that covers statistics, R, graphing, and machine learning. As a source to learn the full breadth of data science...
View ArticlePath to Full Stack Data Science
Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will...
View ArticleThree R Libraries Every Data Scientist Should Know (Even if You Use Python)
Check out these powerful R libraries built by the world’s biggest tech companies.
View ArticlePython leads the 11 top Data Science, Machine Learning platforms: Trends and...
Python continues to lead the top Data Science platforms, but R and RapidMiner hold their share; Almost 50% have used Deep Learning tools; SQL is steady; Consolidation continues.
View ArticleThe Whole Data Science World in Your Hands
Testing MatrixDS capabilities on different languages and tools: Python, R and Julia. If you work with data you have to check this out.
View ArticleWhat you need to know: The Modern Open-Source Data Science/Machine Learning...
We identify the 6 tools in the modern open-source Data Science ecosystem, examine the Python vs R question, and determine which tools are used the most with Deep Learning and Big Data.
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