Crystal Ball
RapidMiner
SAP BusinessObjects Predictive Analytics
Board
SAS Advanced Analytics
IBM SPSS Modeler
Alteryx
KNIME Analytics Platform
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Crystal Ball| Categories |
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| Website | crystalball.tv |
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Pandas| Categories |
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| Website | pandas.pydata.org |
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Based on our record, Pandas seems to be more popular. It has been mentiond 196 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.
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 / about 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 / 4 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 / 4 months ago
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential. - Source: dev.to / 4 months ago
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:. Source: 4 months ago
RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
NumPy - NumPy is the fundamental package for scientific computing with Python
SAP BusinessObjects Predictive Analytics - SAP Predictive Analytics software allows the user to create better and faster predictive results, deliver machine learning at scale using a factory approach and bring predictive insights where people interact _ in business processes and applications.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Board - Unified BI, CPM and predictive analytics software.
OpenCV - OpenCV is the world's biggest computer vision library
