Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Redmine
Asana
Basecamp
Wrike
Teamwork
Teamgantt
Smartsheet
monday.com
Pandas RedminePandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than Redmine. While we know about 219 links to Pandas, we've tracked only 7 mentions of Redmine. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 1 month ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 10 months ago
I’m using redmine. It comes with a learning curve, but has almost endless possibilities. Source: over 1 year ago
Redmine. Its free and has nice features like LDAP authentication, import emails as tickets, etc. Source: about 2 years ago
Planner could work and integrate well with the O365 suite. We use Redmine. It’s low cost/free and is great for small or medium size projects. Source: almost 3 years ago
Redmine - Free, Open Source, Self-hosted. Provides issue management, source control integration, wiki, forums etc. - Source: dev.to / about 3 years ago
No love for Redmine ? https://redmine.org * Ticket tracker. - Source: Hacker News / about 3 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Basecamp - A simple and elegant project management system.
OpenCV - OpenCV is the world's biggest computer vision library
Wrike - Wrike is a flexible, scalable, and easy-to-use collaborative work management software that helps high-performance teams organize and accomplish their work. Try it now.