I will help with state of the art deep learning

I will help you apply machine learning, prediction or classification. This can be applied to numeric data, text, images or speech. The Basic ML includes the following: Define the outcome, analyze and cleaning the data and applying a number of ML algorithms and presenting the results as a report.

All models will be saved and code in Python will be provided that can be used for making predictions on new data.

Standard ML: Same as above but with more iterations for better prediction/classification.

Big ML: Same as above with more iterations and combinations of data like text, images, numeric data or speech and run it locally in Docker containers on Windows or Linux or in the Cloud (Azure, GCP, AWS).

Questions to think about:

Should the model be possible to retrain or not? 

Where should the code for prediction be deployed? On a local machine, in the cloud, on your own deployment or at a cloud set up and owned by me and delivered as an endpoint, API or by email.

Should the data be anonymized for privacy or security reasons?