Python data science essential: Vaex 4.30 . ... Tune into his weekly Dev with Serdar videos for programming tips and techniques and close looks at programming libraries and tools.

Python can be made faster by way of external libraries, third-party JIT compilers , and optimizations with tools like Cython, but Julia is designed to be faster right out of the gate. Julia has a ...

Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the 'human-centered' machine-learning infrastructure it uses for building and deploying data-science ...

PyTorch has many data science applications and can be integrated with other Python libraries, such as NumPy. The library can create computational graphs that can be modified while the program is ...

Overall, the choice between VBA and Python for Excel automation depends on your specific needs. Even though it's outdated, ...

By implementing popular Python packages such as NumPy, SciPy, scikit-learn*, to call the Intel Math Kernel Library and the Intel Data Analytics Acceleration Library (Intel DAAL), Python applications ...

Data science is often cited as one of the main reasons for Python's growing popularity. But while people are definitely using Python for data analysis and machine learning, not many of those using ...

Data management is supported by tools like PostgreSQL, MongoDB, SQLAlchemy, Alembic, ... These 17 Python libraries represent the core tools that every AI engineer should master.

Popular data science tools. Data science tools can cover a broad range of specific use cases, including various programming languages like Python and R, data visualization solutions, and even ...