If you want to do the academic research then Rstudio is preferable otherwise python is better.

You might find Jupyter Notebook is more helpful.

yes both are good for Python being systemic you need to careful and set rule while you have a lot flexibility and more algorithms than you needed, in Python graphs are good base is java and is good for neural networks for both you need to a lot of practice get used to used to method (algorithms )solve some problems and use cases

dont use spyder or any of the IED's until then just work with jyupter or just go anaconda even pychram is required a lot of setting need to be done and sp...

JUPYTER notebook is good for ML. Easy and straight forward to use.

god bless

JUPYTER notebook is good for ML. Easy and straight forward to use.

I will recommend Jupyter notebook. If you are familiar with IDE, Spyder (what I use for python machine learning projects) is very handy and easy to manipulate.

I found both RStudio and Spyder useful for Machine Learning. Spyder provides rich set of python libraries while RStudio offers more R libraries. It depends on what language you are comfortable. I suggest you to use Jupyter notebook for python as it is easy to use and execute a piece of code in each cell sequentially. But you can use Google Colab for free, an online jupyter notebook, as it requires no installation and also provides GPU for faster computation than our normal PC. Here's a tutorial for How to use Google Colab: https://www.geeksforgeeks.org/how-to-use-google-colab/

No right or wrong answer for this one. To become an expert in any field ML included, you should experience all known platforms, techs and stacks. Be agnostic.

I agree with Ahmad Fazreen Baharuden a ML scientist should be familiar with all platforms as far as possible as a ML scientist would likely collaborate with programmer and software engineer who often use various platforms. But one must have a starting point and the easiest to my point of view is Jupyter Notebook for Python.

It depends. If you are going to work on the more Deep Learning sides of Machine Learning you should use Python and Spyder. But if you are going to just look at the things more Statistically and make use of Machine Learning's Statistical side, you should go with R. You should bear this in mind that if you are going to work on big datasets, it is recommended to use Python and Spyder because it has a very good Data Visualization that you can see the form of your data at any point. In my opinion R is for people with less programming experience and specifically for people that their field of study does not directly interact with Programming. But as mentioned above, A data scientist should be familiar with both R and Python.

Go for jupyter notebook.

I think a good data scientist and ML programmer has to be familiar with all the platforms used for that. For Python, Jupyter notebook (or lab) is widely used. When it comes to the comparison between python and R. R has some additional features when dealing with data.

JUPYTER notebook is good for ML. Easy and straight forward to use.

I think both are useful, this is by you to decide which one is more effective for tasks/project? Accordingly, pick the one, in which you already have experience and need of your task or project.

Ravi Verma Both RStudio and Spyder are open source tools, your choice depends on the programming language. If you scientific python (Spyder) or R programming (RStudio). For data visualization with less programming RStudio is preferred. I suggest Spyder(python) cos any one who mastered Python can easily master R

of course both are D.S, but it all depends R is much much before even python is in picture, spyder and all those are tools to learn you can use pycharm , tell you both have own challenges, i have been to fad almost decade back and there is simply no short cuts and what you learn on these is just get comfortable the real time time is much more hard, saying it all depends on yourself and ....

Spyder (Python) is highly recommended experiential if you are new (Beginner) to ML. Jupiter Notebook has lots of ML Add-Ons that will help you speed up your learning process. TensorFlow, Open CV, etc are excellent feature that you can use with the python language. And with its large community you get your way out every bug with a little help on the internet.

this is technology

Both Spyder(Python) and R are good for machine Learning algrithm, but R is highly recommended for statistical analysis. Both are open source and can be launched directly from anaconda navigator. I suggest you to install anaconda navigator first, them you will have R, Spyder, Jypyter and other IDEL to write your machine learning algorithm.

to launch R from anaconda some must be joking just

Se você pensa como um cientista de dados vai de Pycharm (python) é muito mais estável e amigável. Tem muito mais recursos, alem de material na web que facilita a instalação e uso.

I prefer Spyder for ML/DL. It provides MATLAB like environment. Most of the packages required for ML is already installed.

I will recommend you to use Spyder.

Olá!! O Spider é bom, mas o Pycharm é melhor. Vc pode ampliar suas aplicações para o ambiente web facilmente. Faça bom uso.

great and dont understand bit

A ferramenta é muito pratica. Vc pode começar com o Pycharm edition

Usually most of the people describe RStudio as "Open source and enterprise professional software for all R community". An integrated development environment for R, with a console, syntax-highlighting editor that supports direct code execution Publish and distribute data products across your organization. You can use Shiny applications, R Markdown dcouments, Jupyter Notebooks, etc.

The other case is, Spyder defined as: "The Scientific Python Development Environment". It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts.

Differences

RStudio can be categorized as a tech stack, while Spyder can be primarily classified under Integrated Development Environment

In terms of works and Github

RStudio and Spyder are vary powerful tools for datascience. But it seems that Spyder with 465000 GitHub stars and 945 forks on GitHub present more alternatives than RStudio with approximately 290000 GitHub stars and 710 GitHub forks.

I hope it helps.

this is kind of old debate , there are million tools and whichever tools, after being close 9 years still far from perfect , it is just keep practice get used to code first and think of BD

In my opinion Spyder.

opinion are like opinions and cricket teams also full of opinions and dont change your opinion

Both R and Python are very good for ML and Data Analysis. Personally, I will suggest using iPython Jupyter notebook as it will help you documenting your experiments very easily and will increase readability.

and if you are good with c++ you can do that