Webinar: “Speech-to-image generation using Jina”
If you’re involved in machine learning at all, you can’t have missed the plethora of groundbreaking models that have come out in past months. Two of the most hyped models are Whisper, OpenAI’s state-of-the-art speech recognition model, and Stable Diffusion, Stability AI’s groundbreaking image generation algorithm. In our upcoming webinar, Alaeddine Abdessalem, Software Developer at Jina AI, will show us how we can use both of these models to create an end-to-end multimodal application, capable of generating artwork from audio. Whisper allows extremely accurate voice-to-text transcription in
How to Debug a Jupyter Notebook in PyCharm
Making mistakes in your code is a pain, and debugging in Jupyter notebooks can get messy. While Jupyter helpfully displays the full Python traceback, which highlights the lines that have failed, working out exactly what caused the issue in your code can be tricky. I usually end up pulling my code apart in new cells in the same notebook, which creates a huge mess to clean up after discovering the problem. In this blog post, we’ll go over how you can instead use PyCharm’s debugger to track down problems with your code much more efficiently and cleanly. Our example problem We’ll work wi
PyCon Portugal 2022 trip report
This year saw the premier of the first ever PyCon Portugal! With DjangoCon Europe being hosted in Porto this year, the organizers took the opportunity to piggyback off of this conference and set up a PyCon in this beautiful country. I was lucky enough to be selected as one of the speakers, and it was great to be able to contribute to the success of the day in my own small way. Arrival I flew into Porto following Big Data LDN with an easy, direct flight from London. Facing equally long lines to grab a taxi or buy a tram ticket, I opted for the tram, which dropped me off just 15 minutes’ w
Visualizing Geospatial Data in Python
Read an interview with Adam Symington, author of the PythonMaps project, concerning geospatial data visualization and the Python tools used in it.
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 sensitivity or regulations. Such data is used for training machine learning models, testing, and performing quality assurance. In this webinar with Mason Egger, we'll learn about using Synthetic Data, and we’ll learn how to get started creating our own Synthetic Data. Join us on July 2
DataSpell 2022.1 EAP 2: What’s New?
DataSpell 2022.1 EAP 2 is now available, and you can try the newly added features right away. Get the latest version using the ToolBox App by clicking Update – this will update your existing installation. You can also download the new EAP as a standalone version using this button: DOWNLOAD DATASPELL 2022.1 EAP 2 New features overview Bundled Grazie plugin The DataSpell 2022.1 EAP 2 build includes Grazie, a plugin that provides spelling and grammar checks for the text that you write in the IDE. Grazie can provide support for 15 languages (go to Settings | Editor | Natural Languages
DataSpell 2022.1 EAP 1: Support for JupyterHub 2.0, DataSpell Onboarding Tour, and more
DataSpell 2022.1 EAP 1 is open, and we invite you to be among the first to try the freshly added features! Getting the newest version is easy – just click Check for Updates if you’re using the Toolbox App. Alternatively, you can download the new build using this button: DOWNLOAD DATASPELL 2022.1 EAP 1 We are working to include remote Jupyter notebook support in DataSpell. In this EAP, we have support for JupyterHub 2.0 and the ability to copy files between the remote Jupyter server and the local machine. We have also added some fixes that streamline product behavior, such as optimized Ed
DataSpell Has Been Officially Released: A Brand New IDE for Data Scientists Using Python and R
DataSpell is a new IDE by JetBrains designed specifically for those involved in exploratory data analysis and prototyping ML models. DataSpell combines the interactivity of Jupyter notebooks with the intelligent Python and R coding assistance of PyCharm in one ergonomic environment.
DataSpell 2021.3 Release Candidate Is Out!
DataSpell has been in EAP since March 2021, and today is a big day for us – we’re delivering our first release candidate! If you’re using the Toolbox App, it will prompt you to install the update automatically. Otherwise, you can use the following links to install the update manually: macOS (dmg)macOS M1 (dmg)Windows (exe)Linux (tar.gz) You can learn about what’s new in the update below. Jupyter Toolbar First, the Run action in the Jupyter notebook toolbar has been replaced with Run and Select Next, as is in the web-based version of Jupyter. With this action, you can both run th
DataSpell EAP 20 Brings LaTeX Support, Jupyter Console, and More
A fresh DataSpell EAP update is out, and it is packed with some exciting new features! If you’re using the Toolbox App, click Check for Updates. Alternatively, you can download the new build from the DataSpell website. New configuration directory Importantly, the directory, where the IDE stores its settings has changed. If you used an earlier DataSpell EAP build and would like to keep those settings during the update, it’s important to point the new EAP build to the directory with the old settings. The path to the settings directory can be found here. Earlier EAP builds stored settin
Interactive Visualizations in PyCharm and Datalore
The Lets-Plot library is an open-sourced interactive plotting library developed by JetBrains for Python and Kotlin. Its architecture was inspired by the ggplot library for the R language, and is built with layered graphic principles in mind. But what sets Lets-Plot apart from the well-known Matplotlib and Seaborn Python libraries? With Lets-Plot you can produce interactive visualizations, and do it with just a few lines of code. The Lets-Plot library can be easily configured in SciView in PyCharm Professional edition, and comes already pre-installed in Datalore, the online Jupyter notebo
New Features and Enhancements in the R Plugin 2020.3
With the holiday season coming, the R plugin introduces more code assistance and runtime capabilities, UX features, and stability improvements. Try them with the brand new 2020.3 releases of JetBrains IDEs. Use run/debug configurations to manage the way the IDE executes your R code. You can define the command-line arguments of the R script to be executed, the options of the R interpreter, or environmental variables. Configure once and run your script with the same predefined parameters. With the modified R interpreter selector, you can switch between various interpreters and quickly create