Data Science Tutorials

Learn the foundational principles, applications, and practical benefits of variational autoencoders and follow a step-by-step implementation with PyTorch.

Understand how to copy lists in Python. Learn how to use the copy() and list() functions. Discover the difference between shallow and deep copies.

Get started with Apple's DCLM-7B large language model and learn how to set it up, use it, and fine-tune it for specific tasks.

Learn how to set up PyTorch’s torchchat locally with Python in this hands-on tutorial, which provides step-by-step guidance and examples.

The if __name__ == "__main__" block in Python allows you to define code that will only run when the file is executed directly as a script, but not when it's imported as a module into another script.

Learn about QR decomposition, the matrix factorization technique that decomposes matrix A into the product of an orthogonal matrix Q and an upper triangular matrix R.

Learn how to use SQL triggers to automate tasks, maintain data integrity, and enhance database performance. Try practical examples like the CREATE, ALTER, and DROP commands in MySQL and Oracle.

Learn how to round a number to two decimal places in Python for improved precision using techniques like round(), format(), and string formatting techniques.

This tutorial discusses clustered column charts, why Excel is good for creating them, and how to create and customize clustered column charts in Excel.

Learn how to rename local and remote Git branches using either the terminal or the graphical user interface (GUI) of popular clients like GitHub.

Tiktoken is a fast BPE tokenizer developed by OpenAI, primarily used to count tokens for their large language models and ensure efficient text processing within specified limits.

Explore how to master hyperparameter tuning with Optuna. Learn how to define hyperparameters, set up your objective function, and utilize sampling and pruning techniques in deep reinforcement learning.