You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also ...

Following is what you need for this book: This book is aimed at new Python developers with little to no prior programming skills beyond basic computer literacy. The book doesn't require any previous ...

Python has become the most popular data science and machine learning programming language. But in order to obtain effective data and results, it’s important that you have a basic understanding of how ...

Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job. Among the many use cases Python covers, data analytics has become ...

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 ...

Machine learning apps use Python’s memory-managed constructions more for the sake of organizing an application’s logic or data flow than for performing actual computation work.

Nvidia GPUs for data science, analytics, and distributed machine learning using Python with Dask Open source Python library Dask is the key to this. Written by George Anadiotis, Contributor March ...

As previously mentioned, machine learning is part of data science and therefore not strictly confined to a specific role; you can be a data scientist working with machine learning and AI technologies.

Win for Python. This is not a big issue in Data Science, but it does come up in some contexts. Classical computer science data structures, e.g. binary trees, are easy to implement in Python. This can ...

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI ...