General information about the Data Science Virtual Machine product
Data Science Virtual Machine (DSVM) is a cloud server with a ready-made operating system image and pre-installed tools for machine learning developers and data analysts.
With DSVM you can:
- develop applications for chatbots, recommendation services, recognizing objects in photos and videos, speech synthesis and recognition, and prediction services;
- to train the models;
- perform experiments with data.
Tools
Tools are pre-installed in the image for DSVM (more details in their official documentation):
- Python 3.10;
- pip;
- PyTorch;
- TensorFlow;
- JupyterLab;
- Jupyter Notebook;
- Keras;
- scikit-learn;
- NumPy;
- SciPy;
- pandas;
- NLTK;
- OpenCV;
- CatBoost;
- XGBoost;
- LightGBM.
Cost
When using DSVM, only the computing resources of the cloud server are paid under cloud-platform-payment-model.
Before using DSVM top-up balance.
Prices for computing resources can be viewed at selectel.ru.
Create DSVM
Use the Create cloud server instruction.
Select:
- source is a ready-made image of Ubuntu 22.04 LTS Machine Learning 64-bit;
- configuration — with RAM from 2 GB and boot disk capacity from 40 GB. For fast model training, we recommend using GPU Line configurations — they allow up to eight GPUs.
Launch JupyterLab
-
Open the page
http://<ip_address>in your browser.Specify
<ip_address>— the public IP address of the cloud server, can be viewed in control panel under Cloud Platform → Servers → server page → Ports tab → Public IP column. -
Enter the default password:
ikieg2wahmohtahF