Workflow

1

Objective Analyze

At this stage a client tells us everything about his project, shares doubts, fears and dreams. We analyze the problem in order to find solution.

Business analyze Project management
2

Importing Data

Data can come from a variety of sources. You can import CSV files from your local machine, query SQL servers, or use a web scraper to strip data from the Internet. The step is about collecting and importing appropriate data for your project.

Internet Dispersion building Parsing
3

Data Exploration

Obviously, we should explore data before working with it. Data exploration helps to clean data set and select matching algorithms for machine learning.

Seaborn Pandas Matplotlib
4

Baseline Modeling

Baseline is a method that uses heuristics, simple summary statistics, randomness, or machine learning to create predictions for a dataset.

Sklearn
5

Secondary Modeling

Secondary Model is a product of Baseline Module plus several nights with no sleep for our Machine Learning Engineers.

Xgboost Sklearn TensorFlow
6

Integration

The last step is integration. We should integrate machine learning product in a real application, set up and test it thoroughly.

Jupyter Notebook Android SDK iOS SDK

Deliverables:

  • Access to the repository with the source project code
  • Full property rights in relation to the product
  • Fully integrated and working product
  • Collected dataset

Free consultation

Have a project idea? Just give us your email. We will connect with you, and you will see how your idea can benefit with Sheep Apps.