This page features most recent and most popular posts on R.
- Python for data analysis… is it really that simple?!? [Silver Blog]
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 improvement tricks for these solutions are then covered, as are parallel/cluster computing approaches and their limitations.
- Time Series Classification Synthetic vs Real Financial Time Series [Silver Blog]
This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.
- Python and R Courses for Data Science [Silver Blog]
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.
- Plotnine: Python Alternative to ggplot2 [Silver Blog]
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 the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
- Data Science for Managers: Programming Languages [Silver Blog]
In this article, we are going to talk about popular languages for Data Science and briefly describe each of them.
- Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS [Gold Blog]
Data science jobs continue to grow in 2019, and this report shares the change and spread of jobs by software over recent years.
- What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem [Silver Blog]
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.
- Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis [Gold Blog]
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.
- How to correctly select a sample from a huge dataset in machine learning [Silver Blog]
We explain how choosing a small, representative dataset from a large population can improve model training reliability.
- R vs Python for Data Visualization [Gold Blog]
This article demonstrates creating similar plots in R and Python using two of the most prominent data visualization packages on the market, namely ggplot2 and Seaborn.
- Who is a typical Data Scientist in 2019? [Gold Blog]
We investigate what a typical data scientist looks like and see how this differs from this time last year, looking at skill set, programming languages, industry of employment, country of employment, and more.
- Running R and Python in Jupyter [Silver Blog]
The Jupyter Project began in 2014 for interactive and scientific computing. Fast forward 5 years and now Jupyter is one of the most widely adopted Data Science IDE's on the market and gives the user access to Python and R
- Understanding Gradient Boosting Machines [Silver Blog]
However despite its massive popularity, many professionals still use this algorithm as a black box. As such, the purpose of this article is to lay an intuitive framework for this powerful machine learning technique.
- Data Science Projects Employers Want To See: How To Show A Business Impact [Silver Blog]
The best way to create better data science projects that employers want to see is to provide a business impact. This article highlights the process using customer churn prediction in R as a case-study.
- Best Machine Learning Languages, Data Visualization Tools, DL Frameworks, and Big Data Tools [Silver Blog]
We cover a variety of topics, from machine learning to deep learning, from data visualization to data tools, with comments and explanations from experts in the relevant fields.
- SQL, Python, & R in One Platform [Silver Blog]
No more jumping between applications. Mode Studio combines a SQL editor, Python and R notebooks, and a visualization builder in one platform.
- Apache Spark Introduction for Beginners [Silver Blog]
An extensive introduction to Apache Spark, including a look at the evolution of the product, use cases, architecture, ecosystem components, core concepts and more.
- From Data to Viz: how to select the the right chart for your data [Silver Blog]
We offer an interactive, decision tree-style tool, which examines the data you have and proposes a set of potentially appropriate visualizations to represent your dataset.
- Dimensionality Reduction : Does PCA really improve classification outcome? [Gold Blog]
In this post, I am going to verify this statement using a Principal Component Analysis ( PCA ) to try to improve the classification performance of a neural network over a dataset.
- 5 of Our Favorite Free Visualization Tools [Gold Blog]
5 key free data visualization tools that can provide flexible and effective data presentation.
- 7 Simple Data Visualizations You Should Know in R [Silver Blog]
This post presents a selection of 7 essential data visualizations, and how to recreate them using a mix of base R functions and a few common packages.