Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cloud Datalab is a user-friendly interactive platform designed for data exploration, analysis, visualization, and machine learning. This robust tool, developed for the Google Cloud Platform, allows users to delve into, transform, and visualize data while building machine learning models efficiently. Operating on Compute Engine, it smoothly integrates with various cloud services, enabling you to concentrate on your data science projects without distractions. Built using Jupyter (previously known as IPython), Cloud Datalab benefits from a vibrant ecosystem of modules and a comprehensive knowledge base. It supports the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, utilizing Python, SQL, and JavaScript for BigQuery user-defined functions. Whether your datasets are in the megabytes or terabytes range, Cloud Datalab is equipped to handle your needs effectively. You can effortlessly query massive datasets in BigQuery, perform local analysis on sampled subsets of data, and conduct training jobs on extensive datasets within AI Platform without any interruptions. This versatility makes Cloud Datalab a valuable asset for data scientists aiming to streamline their workflows and enhance productivity.
Description
NovoExpress software offers a user-friendly platform for researchers at any expertise level in flow cytometry, facilitating streamlined sample acquisition and analysis. By automating various fluidic operations, it removes tedious and lengthy tasks from the workflow. The system significantly reduces the need for user intervention thanks to its walk-away autosampler feature, along with capabilities for batch analysis, statistical computation, and reporting. This software consolidates sample acquisition and data analysis into a single interface, enhancing user experience. To further boost productivity, users can analyze data as it is being collected, with ongoing sample acquisition occurring simultaneously in the background. The robust compensation tools and straightforward adjustments ensure precise compensation both before and after sample acquisition. Additionally, the batch analysis and reporting functions provide customizable statistical parameters, along with live updates that keep users informed while samples are being processed. Overall, NovoExpress empowers researchers to work more efficiently and effectively in their flow cytometry tasks.
API Access
Has API
No
API Access
Has API
No
Integrations
DataLab
Yes
Google Cloud Platform
Yes
Google Workspace
Yes
Jupyter Notebook
Yes
Integrations
DataLab
No
Google Cloud Platform
No
Google Workspace
No
Jupyter Notebook
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/datalab
Vendor Details
Company Name
Agilent Technologies
Country
United States
Website
www.agilent.com/en/product/research-flow-cytometry/flow-cytometry-software/novocyte-novoexpress-software-1320805
Product Features
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No