ClickUp
Asana
Basecamp
Wrike
monday.com
Teamgantt
Teamwork
Smartsheet
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
htm.java
ClickUp Scikit-learnAll-in-one tool. We use it for docs, project management, tasks, wiki and so on. Awesome product!
Been using Clickup for 8 months now and can't imagine life/work without it ... Very complete and in constant improvement thanks to a great team.
Based on our record, ClickUp should be more popular than Scikit-learn. It has been mentiond 108 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.
Clickup.com — Project management. Free, premium version with cloud storage. Mobile applications and Git integrations are available. - Source: dev.to / 3 months ago
For most teams who don't have the option to subscribe to popular Project Management apps like JIRA, Asana, ClickUp, or Monday, you can make use of GitHub's issue management system to track the bugs in your application. - Source: dev.to / 8 months ago
Create a unified live to-do list from different task builders. We can unify tasks from google doc assignments and clickup tasks. Source: 9 months ago
ClickUp is an all-in-one productivity platform. It’s designed for planning projects, managing tasks, and communicating with team members. Source: 9 months ago
Clickup is perfect for huge teams. Tools for communication, scheduling, and planning are included in the software. It is also visually appealing, allowing you to make graphs, calendars, lists, and charts. ClickUp features fundamental reporting. - Source: dev.to / 9 months ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
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.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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.
NumPy - NumPy is the fundamental package for scientific computing with Python
