Machine Learning

truncate decimal number

How to truncate decimals in Python

When we are working with numbers in Python, we sometimes come across situations where we get numbers like 34.00001, 10000.2358, etc. But in certain situations, these decimal points don’t add value to our calculation and we want to round or truncate the decimals. In this blog, we will see several techniques for truncating decimals using

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error cuda kernal image

Fixed runtimeerror: cuda error: no kernel image is available for execution on the device

When we are using CUDA-enabled libraries like PyTorch or TensorFlow with GPU acceleration at that time we may get the error RuntimeError: CUDA error: no kernel image is available for execution on the device as our code is unable to run on the GPU due to compatibility issues. The error tells us that the CUDA

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Pandas series valueerror

Understanding the ValueError: can only compare identically-labeled series objects in Pandas

The error “ValueError: can only compare identically-labeled series objects” comes in Pandas and specifically when we are dealing with series. This error is quite frustrating when we are new to pandas and performing data analysis. Understanding ValueError: can only compare identically-labeled series objects with code examples. We get “ValueError: Can only compare identically-labeled Series objects”

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notimplementederror loading a dataset

Solving notimplementederror: loading a dataset cached in a localfilesystem is not supported.

The Hugging Face ‘datasets’ library has changed the way data scientists and machine learning developers access and manage datasets. One of the common issues that users face is the `NotImplementedError: loading a dataset cached in a LocalFileSystem is not supported`. This kind of error can really be frustrating when we are in the middle of

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fatal_error_python_image

Solving Fatal Python Error: init_import_size: Failed to Import the Site Module Error

Python is used in various fields from web development to data science. As it is also technology, Python can sometimes encounter errors that can be frustrating for developers. One of these errors is the Fatal Error: init_import_size: Failed to import the site module.” In this blog post, we will explore what causes this error and

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Drop rows with nan

Drop rows with NaN : Pandas

Missing data is a common problem in data science domain. When we are collecting raw data from the environment we get lot of missing values. In Pandas missing values are typically represented as nan (Not a Number). Dropping rows with nan values helps us to maintain the integrity of our analysis by ensuring that only

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