Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
software
|
| gptkbp:allows |
experiment tracking
collaboration on machine learning projects |
| gptkbp:compatibleWith |
gptkb:JupyterLab
|
| gptkbp:developedBy |
gptkb:Amazon_Web_Services
|
| gptkbp:enables |
data exploration and visualization
|
| gptkbp:features |
pre-installed machine learning libraries
|
| https://www.w3.org/2000/01/rdf-schema#label |
Amazon SageMaker Studio Lab
|
| gptkbp:includes |
sample projects
|
| gptkbp:integratesWith |
Amazon SageMaker
|
| gptkbp:is_accessible_by |
web browser
|
| gptkbp:is_available_in |
multiple regions
|
| gptkbp:is_designed_to |
students and educators
simplify machine learning workflows facilitate learning in machine learning |
| gptkbp:is_equipped_with |
integrated terminal
|
| gptkbp:is_known_for |
ease of use
|
| gptkbp:is_part_of |
AWS free tier
Amazon SageMaker ecosystem |
| gptkbp:is_recognized_for |
a_learning_tool_for_AI
|
| gptkbp:is_used_in |
research and development
students developers educators researchers model deployment building and training machine learning models |
| gptkbp:isAccessibleBy |
educational purposes
|
| gptkbp:offers |
tutorials and documentation
customizable environments free access to compute resources version control for notebooks |
| gptkbp:provides |
Jupyter notebooks
community support access to datasets real-time collaboration features interactive coding environment notebook sharing capabilities access_to_GPU_instances |
| gptkbp:requires |
AWS_account_for_advanced_features
|
| gptkbp:suitableFor |
data scientists
machine learning practitioners |
| gptkbp:supports |
gptkb:PyTorch
Python programming language TensorFlow scikit-learn data preprocessing model evaluation data import from various sources |