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You can use the LeakyRelu layer, as in the python class, instead of just specifying the string name like in your example. It works similarly to a normal layer. …

The input shape for an LSTM must be (num_samples, num_time_steps, num_features). In your example case, combining both cities as input, num_features will be 2x3=6. If you lump all your 365 time steps …

You don't really need to implement an algorithm to achieve this. There are a few tools that will do this for you. You can get the data assigned to buckets for further processing using Pandas, or simp …

Simple explanation with images We know that an activation is required between matrix multiplications to afford a neural network the ability to model non-linear processes. A classical LSTM cell alrea …

that includes the GPU version of Tensowflow like this: conda create --name gpu_test tensorflow-gpu # creates the env and installs tf conda activate gpu_test # activate the env python …

LSTM layers require data of a different shape. From your description, I understand the starting dataset to have 3125 rows and 1000 columns, where each row is one time-step. The target variable should …

Don't worry - your hard-earned Python skills are still important ;) Tableau is not a replacement - it is essentially a means of sharing your insights/findings. … Watch this video for a good overview of everything it can do, and how it connects to Python (and R/MatLab). There is just a bit of boiler plate code around your normal Python code. …

The output of a neural network will never, by default, be binary - i.e. zeros or ones. The network works with continuous values (not discrete) in order to optimise the loss more freely in the framewor …

Given you have images stretched out as columns in a table with ~48,500 rows, I am assuming you have the raw images that are 220x220 in dimension. You can use a function available via OpenCV called inp …

I personally think that the general idea of optimising your model with different random seeds is not a good idea. There are many other, more important, aspects of the modelling process that you can wo …

Also that this is done again in Python. My solution will require Python 3, although the principle could be applied to Python 2. … # True That \N is pretty cool (and works in python 3.6 inside formatted strings too)... it basically allows you to pass the Name of a character, as per Unicode's specification. …

As you are working on image classification and would also like to implement some data augmentation, you can combine the two AND load the batches directly from a folder using the mighty 'ImageDataGener …

I can imagine a value of -1 consumes all available resources as and when they become available. Depending on which function you are talking about, it seems data is copied for each of the jobs, which c …

I have done this before and didn't find a default implementation - the StratifiedKFold and RepeatedStratifiedKFold are only documented to work with classes. The way I ended up doing it was not quite …

Such models can be constructed quite easily with Python, using the statsmodels package, which has a nice implementation. …