LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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Weights & Biases
neptune.ai
Algorithmia
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Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
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WEKA
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Based on our record, Pandas seems to be more popular. It has been mentiond 198 times since March 2021. 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 / 11 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 / 5 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
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
NumPy - NumPy is the fundamental package for scientific computing with Python
Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
OpenCV - OpenCV is the world's biggest computer vision library