Python Functions, Lambdas, and Map/Reduce (1.5)

Python functions, lambdas, and map/reduce allow you to take your Python programming to the next level. This video introduces functions, lambdas, and map/reduce for Python programming language directed towards deep learning with Keras and TensorFlow.

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#Python #Tensorflow #Keras #map #reduce #mapreduce

[seppel]

I do find your videos easy to follow. It is a true service to all of us that somebody takes his time to build up the understanding of more complex things by starting with the basics. Currently following your 2017 series of Neural Networks with python... and it is great! TY so much!

[moosagaming]

Superb delivery!
Therefore, few minutes mean a lot everytime.
God bless you Professor

[aatt]

I especially appreciate the comparison and contrast of multiple ways to accomplish the same output, which clarifies confusion that I run into looking at different programs. Dr. Heaton not only is a great teacher but a generous soul for putting all of his class materials on Youtube for all to see and learn from. str=process_string(" thank you "), print(f' "{str}" ') from California.

[jessemccarthy]

Hey Jeff, just curious about the effects of using map/reduce for large data sets. Because of its interface it seems that it necessarily would have to call the provided function for each datum; is this true? The only possible means around this I can think of would be to use the dissasembly of a the provided function. Depending on the operation I guess I could have a negligable impact, but wouldn't making a single function accepting the data directly whether streaming or otherwise, and being able to operate on multiple data using SSE-like intructutions, be a better paradigm for machine learning?

[harshitshukla]

Thank you Sir..for these videos, I have watched you previous series too..still your way of teaching makes me come by again and again.Thanks for all of it..Keep uploading ..it makes my day

[Didanihaaaa]

thanks. good job. easy to understand. (y)

[rchuso]

"filter" looks like a direct mapping to the array handling feature in Fortran (under the covers?). Something like: indices = PACK([(i, i=1, SIZE(l))], l > 5) - Yea, Fortran is more verbose, but it's fast.

[pfever]

1:27 to be precise, when a return value is not specified in python it returns None