Python offers developers a standard library, as well as a massive collection of components ranging from individual modules to packages and application development frameworks, all available from the Python Package Index. By using libraries, a development team doesn’t build everything from scratch. Instead, developers can use pre-built elements to build features in areas such as image processing, machine learning, and data visualization.
python-libraries
Data science
Quick guide to data cleaning with examples
Data cleaning is a critical part of every data science project, there’s no doubt about it. But here’s something you should know: preparing data for proper analysis is often [...]
- Dec, 2019
- 9 min
Basics
What is Python used for? Key benefits and examples across 3 industries
What do Netflix, Facebook, Amazon, Dropbox, and Instagram have in common? Aside from being tech giants, they’re all built with the same core technology: Python. Created almost three decades [...]
- Jun, 2019
- 8 min
Data science Python
24 Python machine learning libraries for data science projects
Python is one of the most popular languages among data scientists and web developers today thanks to a large number of libraries that do just about anything, including machine [...]
- Jan, 2019
- 5 min
Data science Python
8 best Python Natural Language Processing (NLP) libraries
Natural language processing (NLP) is a field located at the intersection of data science and Artificial Intelligence (AI) that – when boiled down to the basics – is all [...]
- Jun, 2018
- 7 min
