Based on our record, Pandas seems to be a lot more popular than datarobot. While we know about 198 links to Pandas, we've tracked only 1 mention of datarobot. 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.
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 15 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 8 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
To predict what we would have expected, we used the models and approach we developed to predict the knockout stage of the Champions League using data provided by Data Sports Group. We used DataRobot’s models to predict which team would win each match to simulate the final nine matchdays 10,000 times. For each team, we calculated the average number of wins, draws and losses over those 10,000 seasons to build an... Source: about 1 year ago
NumPy - NumPy is the fundamental package for scientific computing with Python
RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Statista - The Statistics Portal for Market Data, Market Research and Market Studies
OpenCV - OpenCV is the world's biggest computer vision library
H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.