Programming Python vs R
To finish reading, please visit source site
Read more
Tag: R
Picking an Analytic Platform
Summary: Picking an analytic platform when first starting out in data science almost always means working with what we’re most comfortable. But as organizations grow larger there is a need for standardization and for selecting one, or a few analytic tools. Picking an analytic platform when first starting out in data science almost always means working with what we’re most comfortable. That in turn almost always means whatever we used in college (or your certificate course) be it R, […]
Read more
Characteristics of Good Visual Analytics and Data Discovery Tools
Visual Analytics and Data Discovery allow analysis of big data sets to find insights and valuable information. This is much more than just classical Business Intelligence (BI). See this article for more details and motivation: “Using Visual Analytics to Make Better Decisions: the Death Pill Exa…“. Let’s take a look at important characteristics to choose the right tool for your use cases. Visual Analytics Tool Comparison and Evaluation Several tools are available on the market for Visual Analytics and Data […]
Read more
R, Python or SAS: Which one should you learn first?
Python, R and SAS are the three most popular languages in data science. If you are new to the world of data science and aren’t experienced in either of these languages, it makes sense to be unsure of whether to learn R, SAS or Python. Don’t fret, by the time you’re done reading this article, you will know without a doubt which language is the right one for you. Overview R – R is the lingua franca of statistics. It is a […]
Read more
What are the Big Guys Using?
Summary: The largest companies utilizing the most data science resources are moving rapidly toward more integrated advanced analytic platforms. The features they are demanding are evolving to promote speed, simplicity, quality, and manageability. This has some interesting implications for open source R and Python widely taught in schools but significantly less necessary with these more sophisticated platforms. We continue to be dazzled, and perhaps rightly so, by the advances in deep learning and question answering machines like Watson. And […]
Read more
Open Source Deep Learning Frameworks and Visual Analytics
Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist. What is Deep Learning and Artificial Neural Networks? Deep Learning is the modern buzzword for artificial neural networks, one of many concepts and algorithms in machine learning […]
Read more
Why R is Bad for You
Summary: Someone had to say it. In my opinion R is not the best way to learn data science and not the best way to practice it either. More and more large employers agree. Someone had to say it. I know this will be controversial and I welcome your comments but in my opinion R is not the best way to learn data science and not the best way to practice it either. Why Should We Care What […]
Read more
Best practices of orchestrating Python and R code in ML projects
Today, data scientists are generally divided among two languages — some prefer R, some prefer Python. I will not try to explain in this article which one is better. Instead of that I will try to find an answer to a question: “What is the best way to integrate both languages in one data science project? What are the best practices?”. Beside git and shell scripting additional tools are developed to facilitate the development of predictive model in a multi-language environments. For […]
Read more
How to Execute R and Python in SQL Server with Machine Learning Services
Introduction Did you know that you can write R and Python code within your T-SQL statements? Machine Learning Services in SQLServer eliminates the need for data movement. Instead of transferring large and sensitive data over the network or losing accuracy with sample csv files, you can have your R/Python code execute within your database. Easily deploy your R/Python code with SQL stored procedures making them accessible in your ETL processes or to any application. Train and store machine learning models […]
Read more