jamovi
JASP
BlueSky Statistics
Jupyter
Statista
Montecarlito
datarobot
IBM ILOG CPLEX Optimization Studio
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
Figure Eight
jamovijamovi has one of the most attractive user interfaces. Even the colors used for window-dressing match the default colors for its graphs. Like JASP, its dialogs provide instant results as each item is checked off. That immediate feedback feels great! Corrections to data values are also immediately reflected in each piece of output that would be affected. However, this also means that you can't do one step, restructure the data, then do another since jamovi requires each step to have the same data structure. SPSS, Minitab, BlueSky Statistics, and JMP can all do such common data-wrangling tasks. So, if you restructure your data a lot, you'll need to do that with another tool and read the data in separately for each structure. jamovi's menus start out very sparse and you extend them by downloading needed parts later. This is the opposite of similar tools like SPSS, Minitab, and BlueSky Statistics, which show all their capabilities upon installation. That makes it good for beginners who avoid the others' complex menus. Regarding analytic methods, jamovi has the most popular statistics. The main topics it lacks are quality control and machine learning/AI. Also, it cannot save models for making predictions on a different dataset.
Based on our record, NumPy seems to be more popular. It has been mentiond 119 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.
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
JASP - JASP, a low fat alternative to SPSS, a delicious alternative to R.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
BlueSky Statistics - BlueSky Statistics is a fully featured statistics application and development framework built on...
OpenCV - OpenCV is the world's biggest computer vision library
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.