Machine learning projects can range from small datasets and standard algorithms, to much larger projects that use neural networks engines with massive datasets.
So how does one get started? What you need is a data pipeline that brings in all your components working together. A data pipeline is a set of actions that extracts data, then helps build predictions and finally output.
The following machine learning infographic illustrates the two types of data pipelines, featuring the best tools to use for each step of the process. This infographic includes well-loved tools like Hadoop, TensorFlow, and PyTorch. We hope that this helps you streamline processes for your complex projects.