What tools are needed to develop a ML environment?

To develop a machine learning (ML) environment, one needs a range of tools. These tools are required for various tasks such as data pre-processing, data visualization, model training, and deployment. Some necessary tools include programming languages such as Python or R, frameworks such as TensorFlow or PyTorch, cloud storage options such as Amazon S3 or Google Cloud Storage, and IDEs such as Jupyter Notebook or Spyder for code development. Other tools may include SQL or NoSQL databases for data storage, data analysis tools like Excel or Tableau, and version control systems such as Git. ML environments also require high-performance computing resources like multi-core CPUs, GPUs, and TPUs for faster training and better model accuracy.

This mind map was published on 12 June 2023 and has been viewed 154 times.