Introducing the Revamped Datalore UI – Built for Focus
Today, we’re introducing a redesign that aims to make Datalore notebooks appear simpler, cleaner, and ultimately more zen.
Extra Datalore Credits for Flexible CPU and GPU Computing Power
Different analytical tasks have different computing requirements. Depending on the complexity of your project, the computing power you need can vary significantly from month to month. That's why we're introducing the option to purchase extra Datalore credits. Read more.
How to Read From MySQL Database to pandas With Datalore
Reading data from a MySQL database to a pandas dataframe can be intimidating. Establishing a connection, keeping the credentials safe, creating an SQL query within a string variable, and saving the result to pandas is not a trivial task.
New in Datalore 2023: Run API and a Number of Performance Improvements
Since January 2023, we have rolled out a number of new features for our Community and Professional users. The list includes the long-awaited Datalore Run API, a more robust reactive kernel, a whole array of Powerful CPUs and GPUs, Datalore credits for Professional users, and a number of performance improvements.
Can Data Science Collaboration Be Secure? [New Datalore Case Study]
Working with financial data is not a trivial task, as you can’t just access a production database or a data lake, download the data, and work on it. You have to ensure secure access to the data and produce insights that are easy to share as well.
How to Work With Git in Datalore
Learn how to install Git repositories, edit the content of these repositories, and version your work with Datalore.
Introducing 8 Extremely Powerful CPUs and GPUs to Datalore
Today we are introducing 8 new powerful CPU and GPU machines to Datalore Professional and a flexible new way to spend your computation quota – Datalore credits!
A Comparison of Python vs. R for Data Science
Learn about the difference between the typical use cases of R and Python for data science. Discover the tasks most suited to the languages, as well as how to use them in Datalore.
R vs. Python: Key Differences
Discover the similarities and differences between R and Python. Programming styles, data visualization and libraries for each programming language are covered.
How to Prepare Your Dataset for Machine Learning and Analysis
Learn about data preparation for machine learning and analysis, and avoid some of the most common problems real-world data can throw at you.
Webinar: I Can’t Believe It’s Not Real Data! An Introduction to Synthetic Data
Easy access to relevant, safe data is a major bottleneck hindering developers and data scientists. But what if you could generate your own accurate, privacy-protected, shareable data? Synthetic data can provide an inexpensive alternative to real sets of data that can’t be used due to its se…
New in Datalore: Chart Cells, Spelling and Grammar Checking, Initialization Scripts, and More
Greetings from the Datalore team! Does the #Tesla stock price depend on Elon Musk’s mood? In this newsletter, we’ll share a new tutorial for sentiment analysis and talk about the new features that can improve your daily workflow in Datalore. Chart cells Could you imagine that working with v…