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Best platform for Big data analytics for beginners - AWS vs Azure vs Google cloud

Hello everyone,

I have 12+ experience in Java enterprise programming and a beginner in Big data analytics.
Currently started learning Python and going through blogs related to analytics, statistics, modelling etc.
I have a mac book which based on my analysis so far is not best suitable for running machine learning or data intensive algorithms using Python.
I dont want to spend too much of money for buying expensive machines with GPUs before i get hands on with the technologies.
I am thinking of subscribing to any of online cloud services like AWS, Azure or Google cloud.
However would like to check which would be a suitable bet for a beginner who likes to run some samples and test algorithms with lots of sample data set and sample packages or projects which i can download online?
Would like to check which one gives more
i) packages and suits to learn
ii) cost effective
iii) Relatively simple learning curve
iv) Potential to rule the market in future for analytics.

Would be greatful if i can get any suggestions or any blogs written on this topic already.

Sorry this is my first post in this community and not sure this is already discussed before.

Thank you in advance.

Regards
Subash

Tags: AWS, Azure, Google Cloud

Views: 3647

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Of course, it depends.  

For personal projects or projects from scratch, Google's GCP is compelling on price, and with their products.  Their training with Google Code Labs and online solutions is compelling.  It helps simplify the data engineering.  AWS is relatively harder to use, but they have the dominant market share.  Both are a result of being the first mover.  Azure is in between but has headway into certain enterprises.  

Subash,

I am currently taking an in-person class for Data Analysis. We are supposed to use Anaconda on our home machines but I ended up switching to Notebooks on Azure. (notebooks.azure.com)

It is a nice (and free) environment to work with R and Python within a Jupyter notebook. I highly suggest it.

I would also try out Data Science Experience.  It has free R and Python Jupyter notebook environment as well and and it has a lot of other bells and whistles: collaboration features, streams, modelling, spss integrations, data catalog and more. 

https://datascience.ibm.com/

Here is a tutorial showing how to do predictive analytics with the data science experience platform: https://www.littlemissdata.com/blog/predictive-analytics-tutorial-p...

Hi Tom. Are you using RStudio inside notebooks or is Jupyter the IDE for R?  Are there any issues using Jupyter with any R packages etc?

Tom O'Neil said:

Subash,

I am currently taking an in-person class for Data Analysis. We are supposed to use Anaconda on our home machines but I ended up switching to Notebooks on Azure. (notebooks.azure.com)

It is a nice (and free) environment to work with R and Python within a Jupyter notebook. I highly suggest it.

Within Azure, Jupyter is the IDE for R.

RStudio is much better because it has an actual GUI and type-ahead. Jupyter is great for python because it allows you to have an organized (yet limited) IDE with source control.



Blaine Bateman said:

Hi Tom. Are you using RStudio inside notebooks or is Jupyter the IDE for R?  Are there any issues using Jupyter with any R packages etc?

Tom O'Neil said:

Subash,

I am currently taking an in-person class for Data Analysis. We are supposed to use Anaconda on our home machines but I ended up switching to Notebooks on Azure. (notebooks.azure.com)

It is a nice (and free) environment to work with R and Python within a Jupyter notebook. I highly suggest it.

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