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

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

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

Baseline Modeling

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


Secondary Modeling

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

Xgboost Sklearn TensorFlow


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


  • 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 contact you, and you will see how your idea can benefit with Sheep Apps.