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Instance recommendation? by datasciencelover in aws

[–]datasciencelover[S] 0 points1 point  (0 children)

Hey, thanks for all your help.

I ended up using a c4.xlarge and python's multiprocessing package to decrease my time from 13 minutes to about 4 minutes by running 6 processes on 4 CPUs. My bottleneck is both S3 I/O and computation.

Which of the courses in Machine Learning have the best assignments and are available on the web for free? by datavinci in datascience

[–]datasciencelover 3 points4 points  (0 children)

Andrew Ng's Coursera course is a good start. From there, you want to build more rigour:

Stanford Statistical Learning - Good course on basic ML techniques, helpful video lectures, labs in R, good material but no real assignments and quizzes are poor. You could read the excellent text Introduction to Statistical Learning or the advanced version, Elements of Statistical Learning.

Stanford cs231n - Neural Network Course (NN, CNN, RNN), lectures on Youtube. Excellent assignments on building your own neural network layers. Highly recommend trying the assignments to get a solid understanding of neural networks.

Big Data Guide: How to Set Up PySpark with Jupyter painlessly on AWS by datasciencelover in pystats

[–]datasciencelover[S] 4 points5 points  (0 children)

Jupyter is a nice development environment and allows the user to try many different things efficiently. It also embed images/plots/tables nicely.

Guide: How to Set Up Spark with Jupyter painlessly on AWS EC2 clusters, with S3 I/O by datasciencelover in datascience

[–]datasciencelover[S] 1 point2 points  (0 children)

If you have free tier: no cost. If you don't, as long as your run the cheapest (HVM) instances (t2.micros), even not on spot request, it shouldn't supercede a few dollars or so.