Based on our record, Jupyter seems to be a lot more popular than RapidMiner. While we know about 205 links to Jupyter, we've tracked only 3 mentions of RapidMiner. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
RapidMiner: A data science platform that offers an automated EDA process, including data preprocessing, visualization, and analysis. Source: about 1 year ago
I hope this blog empowers you to start digging deeper into Apache Arrow and helps you to understand why we decided to invest in the future of Apache Arrow and its child products. I also hope it gives you the foundations to start exploring how you can build your own analytics applications from this framework. InfluxDB’s new storage engine emphasizes its commitment to the greater ecosystem. For instance, allowing... - Source: dev.to / over 1 year ago
Rapidminer - RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics. Link - https://rapidminer.com/. - Source: dev.to / over 2 years ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 17 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 28 days ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 23 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.