The field of data science has seen enormous growth over the last few years. Organizations increasingly leverage data as a strategic asset that data scientists turn into meaningful insights. These days, data science and machine learning are essential to software products that need to classify information, and deliver personalized experiences and unique interactions with users.
R and Python are popular programming languages in data science because they combine text with code to clean and explore data for reproducible insights. As data science and machine learning are iterative processes for testing new ideas, Git and GitHub are ideal tools for tracking changes and working together.
Git and GitHub help data scientists:
- Store projects in GitHub repositories to organize work, track changes, and provide a clear and well documented path for analysis
- Integrate with popular editors like RStudio, PyCharm, and Atom. You can also edit files directly on GitHub
- Identify, assign, and keep track of team tasks with issues and project boards
- Talk through ideas, discuss details, and conduct reviews with pull requests
- Run automated builds and tests for more complex projects to reduce bugs and maintain quality
Collaborate and share
- Collaborate with product developers and integrate machine learning features into their projects through forks
- Host your rendered R or Jupyter notebooks directly from your GitHub repositories
- Allow others to validate and verify your findings or learn from your experiences
Our data science webcast series will explore the different ways data scientists use Git and GitHub:
GitHub for data scientists: on February 21 we will kick-off this series by sharing best practices on how GitHub can be used in a data science workflow.
Conversation with Pirelli: on March 22, our second webinar will feature Carlo Tornai, Global Director of Digital Product Development at Pirelli.
How GitHub is using data science: on April 26, the third and final webinar will introduce you to the GitHub data science team to discuss how we are using insights to improve the GitHub experience.
We look forward to seeing you there!