RStudio for quick prediction prototyping
Updated September 06, 2021
RStudio for quick prediction prototyping
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with RStudio
Very few of us are getting into predictions using Machine Learning and Data Science. We use Rstudio to program our algorithms. There are only a handful of people in the whole organization who use Rstudio right now. We use it in pockets, and do the proof of concepts with Machine Learning using R.
- We use it for a quick visual representation of data
- We do exploratory data analysis to understand data
- We do predictions using RStudio
- When we have to run 100 iterations using more than 10000 records, RStudio gets stuck or takes a very very long time to respond
- Generating a pdf report from an RMD file is very difficult from RStudio.
- Generating a pdf report in RStudio cloud is straightforward and inbuilt.
- RStudio is free and it's easy to start using it
- It's easy to install new libraries and start using them seamlessly
- The installation of some libraries is challenging, especially when they depend on a lot of other libraries.
- RStudio crashes when there is a clash between libraries somehow.
I have used Jupyter notebooks. I have used the cloud version of RStudio extensively. I program mainly in R as we have some libraries on Microstrategy which are in R. So, R was a natural choice for prototyping. I also use Jupiter Notebook for python programming. But, I use this less often than R.
Using RStudio
10 - We are a varied group of individuals coming from different backgrounds. Some are data scientists, some are Ph.D. doctors, some are programmers like me. All of us work on business problems, which present a lot of data which does not have immediate meaning to the business. We try to run predictions based on that data.
10 - We are a bunch of programmers who use Rstudio. We do not really support the software, but we use it. We do help each other when we run into issues or get stuck into specific programming needs using R. Most of us have some kind of programming experience. There are some Ph.D. scientists who also program on RStudio.
- Running quick predictions based on the data at hand
- Representing data using graphs and charts
- Exploratory data analysis using RStudio
- We use it for scatterplot matrices
- We use it to quickly see the dependencies of various predictors
- We check multicollinearity between our input columns
- We hope to use it on a production run basis on cloud
- We need to be able to scale our prototype solution to larger sets of data
- We wish to have stable models, using Rstudio, which can be dynamic based on new data
Evaluating RStudio and Competitors
- Price
- Vendor Reputation
- Third-party Reviews
It's free and easy to use. That's most important, as it gives us the flexibility to switch to something else for our prototyping needs.
If we had to do it again, we would like consider a product which is cloud first. We currently use RStudio Cloud, which is close to what we want in the future. But how much can we scale is the question. We have not really tested that yet. We would assume there are options to use it on cloud vendors such as Azure and AWS.
RStudio Implementation
- Implemented in-house
Change management was minimal
RStudio Support
| Pros | Cons |
|---|---|
Problems get solved | None |
I did not purchase premium support. I just use the cloud-based and RStudio IDE.
Using RStudio
| Pros | Cons |
|---|---|
Like to use Relatively simple Easy to use Technical support not required Well integrated Consistent Quick to learn Convenient Feel confident using Familiar | None |
- Generation of HTML reports out of the RMD
- quick help files for any functions
- A quick view of data files
- The loading of files with lot of data takes a lot of time
- Generation of pdf report from RMD is not very easy.