A Beginner’s Guide to Python Machine Learning and Data Science Frameworks
Python has become one of the most popular programming languages for machine learning and data science.
It is a powerful language with many libraries and frameworks that make it easy to build complex models and analyze large datasets. In this beginner’s guide, we will take a look at some of the most popular Python machine learning and data science frameworks.
- NumPy is a library for scientific computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a large collection of mathematical functions to operate on these arrays. NumPy is a core library for many other Python machine learning and data science libraries.
- Pandas is a library for data manipulation and analysis. It provides powerful data structures such as DataFrame and Series that make it easy to work with tabular data. Pandas also has many tools for data cleaning, merging, and reshaping.
- Matplotlib is a library for data visualization. It provides a wide range of plotting functions to create high-quality, publication-ready graphs and charts. Matplotlib can be used to create line plots, scatter plots, histograms, bar plots, and many other types of visualizations.
