What are some strategies to reduce memory usage when working with large datasets in Jupyter Notebook?

Several strategies can help: 1) Use data types that require less memory (e.g., `int8` instead of `int64` if your values allow). 2) Load only the necessary columns or rows of a dataset using techniques like `pandas.read_csv(usecols=[...])` or chunking. 3) Delete unnecessary variables using `del variable_name` to free up memory. 4) Use generators instead of lists for large sequences. 5) Consider using libraries like `dask` for out-of-core computation.