Python Libraries Every Data Scientist Must Use in 2024

In 2024, Python libraries essential for data scientists include Pandas, NumPy, and Matplotlib for data manipulation and visualization. Scikit-learn remains a cornerstone for machine learning, while TensorFlow and PyTorch dominate deep learning. Jupyter Notebooks facilitate interactive data analysis, and Seaborn enhances statistical graphics. Libraries like SciPy offer scientific computing capabilities, and XGBoost and LightGBM are vital for boosting algorithms. For natural language processing, NLTK and SpaCy are indispensable. Data version control is streamlined with DVC, and data processing is optimized with Dask. These libraries collectively empower data scientists to efficiently handle, analyze, and model data across diverse applicat

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