Core features of open source machine learning libraries

At their core, machine learning libraries are just software libraries written in different programming languages. What makes them different from other software libraries are the functions they support. In general, most ML libraries have support for the following key features via different library sub-packages:

• Data manipulation and processing: This includes support for different data tasks such as loading data of different formats, data manipulation, data analysis, data visualization, and data transformation.
• Model building and training: This covers support for built-in machine learning algorithms as well as capabilities for building custom algorithms. Most ML libraries also have built-in support for the commonly used loss functions (such as mean squared error or cross-entropy) and a list of optimizers (such as gradient descent or adam) to choose from. Some libraries also provide advanced support for distributed model...