The numpy.ndarray.shape() returns the shape of our ndarray as a tuple. For a 1D array, the shape would be (n,) where n is the number of elements in your array.For a 2D array, the shape would be (n,m) where n is the number of rows and m is the number of columns in your ...
How does python numpy.where() work? How does numpy.std() method work? Is there a multi-dimensional version of arange/linspace in numpy? How to copy data from a NumPy array to another? Why does corrcoef return a matrix? Comparing numpy arrays containing NaN shuffle vs permute numpy Partitio...
Frozen parameters are those that do not compute gradients. Hence, it is useful to freeze the parameters when we know before hand that these parameters are not required to calculate the gradients in the tensor. Also in finetuning, we freeze the model completely and computation is done only to ...
fast and easy to use. It was developed by François Chollet, a Google engineer. Keras doesn’t handle low-level computation. Instead, it uses another library to do it, called the “Backend.
where the line at the start of the box goes to the minimum value and the line at the end of the box goes to the maximum value. The longer the whiskers, the larger the variability may be in the data set. Any circles or points outside of the whiskers represent outliers in the data....
Scratch|Stability.AI|SSM & MAMBA|RAG Systems using LlamaIndex|Getting Started with LLMs|Python|Microsoft Excel|Machine Learning|Deep Learning|Mastering Multimodal RAG|Introduction to Transformer Model|Bagging & Boosting|Loan Prediction|Time Series Forecastingn|Tableau|Business Analytics|Vibe Coding in ...