What's included

• Data collection

  Very often the most complicated and time-consuming problem in AI development is related to data finding and collection of it. When you have data, then 70% of job is done, so I can help with picking up the data and with it automated collection using web scrapers.

• Exploratory Data Analysis (EDA)

  When the data is already collected, then in 100% of cases, it should be preprocessed and analyzed to get a better understanding of what we have right now, which includes how much sparse it is, how well existing features are correlated, how well they are normalized, how they are distributed, getting info about labels if we have any, and providing full statistical analysis of existing data, so we can decide which pipeline is the most suitable for us.

• Pipeline creation

  After EDA is completed, now we have enough information to choose which pipeline to choose and what type of modifications to our data should be done. Here I also include automated features generation if it is needed.

• Model selection

  Based on the specifics of tasks and goals that we are trying to achieve I will choose the most competitive model, which will be suitable for you.

• Model development

  In this section, the model will be developed from scratch using existing ones' architecture or we will use a ready model, on which further actions will be taken

• Model training and evaluation

  Here we have 2 options: * Model is already pretrained * Model is not pretrained at all In the first case, we will fine-tune it using our dataset via modern validation techniques and make automated hyperparameter selection. In the second case our data will be used to train our model from zero. After it is trained, I will evaluate our model accuracy and get understanding whether expectations about the models were achieved or not.

• Draft version deliverable

  Client will get a draft version based on client requirements and I will be looking for his feedback on what is needed to be updated / added / deleted.

• Final version deliverable

  Based on the feedback of a draft version, client will get a final product - dockerized AI model, which he will be instructed of how to run and use.

• Model Deployment

  Productionize the trained model so it can be used