Exploring Open-Source ML Libraries

There is a wide range of machine learning (ML) and data science technologies available, encompassing both open-source and commercial products. Different organizations have adopted different approaches when it comes to building their ML platforms. Some have opted for in-house teams that leverage open-source technology stacks, allowing for greater flexibility and customization. Others have chosen commercial products to focus on addressing specific business and data challenges. Additionally, some organizations have adopted a hybrid architecture, combining open-source and commercial tools to harness the benefits of both. As a practitioner in ML solutions architecture, it is crucial to be knowledgeable about the available open-source ML technologies and their applications in building robust ML solutions.

In the upcoming chapters, our focus will be on exploring different open-source technologies for experimentation, model building, and the development...