Software Alternatives, Accelerators & Startups
Register | Login

teamdeck VS Scikit-learn

Compare teamdeck VS Scikit-learn and see what are their differences

FreshBooks
The ideal accounting software for small business owners. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

teamdeck logo teamdeck

Teamdeck is a SaaS resource management tool with resource scheduling, leave management, time tracking and timesheet, and customizable reports features. Selected by Hill-Knowlton, Stormind Games, Wunderman Thompson. $3.60/per member.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • teamdeck Landing page
    Landing page //
    2023-10-18

Teamdeck is a web-based, integrated resource scheduling, time tracking, and leave management tool with customizable reporting. In many companies, our tool replaced Resource Guru, Mavenlink, Monday.com. It is an essential tool for managing resources and monitoring time spent on tasks and projects. In general, using just spreadsheets to manage bookings and schedules can be dangerous. Not being able to track time or using multiple, separate time tracking tool will not give a clear picture of the whole either. In fact, development teams lose an estimated $18,000 plus every year when they do not correctly and accurately track their time.

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

teamdeck

Website
teamdeck.io
Pricing URL
Official teamdeck Pricing
$ Details
freemium $3.99 / Monthly (per user per month)
Platforms
Browser iOS Android JavaScript
Release Date
2017 July
Edit details

Scikit-learn

Website
scikit-learn.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

teamdeck features and specs

  • Resource Planning
  • Time Tracking
  • Availability Management
  • Leave Management
  • Integrations
    SageHR, Podio, Slack, Zapier
  • RESTful API

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

teamdeck videos

+ Add

Manage your team’s work with Teamdeck

More videos:

  • Demo - How to make the most out of TEAMDECK DEMO ORGANIZATION?
  • Tutorial - How to manage resources with Teamdeck?

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to teamdeck and Scikit-learn)

teamdeck

Scikit-learn

Project Management
100 100%
Project Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Time Tracking
100 100%
Time Tracking
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using teamdeck and Scikit-learn. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare teamdeck and Scikit-learn

teamdeck Reviews

21 Time Tracking Tools To Manage Your Workday
Within the platform. Teamdeck offers team scheduling, workload management, time tracking, timesheets, project planning, availability management, and a few other features. Thanks to Teamdeck you can assign people to projects on a calendar and define their hourly schedule based on their availability, job position, skills, and your own defined attributes (ie. seniority).
Source: hive.com
50 Best Project Management Tools for 2019
Teamdeck offers a complete solution for companies to deliver projects faster. It is an essential pm software for managing resources and monitoring time spent on tasks and projects. With Teamdeck you can book your employees on different projects and create accurate timesheets with one-click time tracking.
Source: www.proofhub.com

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than teamdeck. While we know about 31 links to Scikit-learn, we've tracked only 1 mention of teamdeck. 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.

teamdeck mentions (1)

  • Looking for a Uk Lead Developer/tech Co-Founder
    Also a quick Google of "team decks" showed this. Source: almost 4 years ago

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    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 / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    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 / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    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 / almost 2 years ago
View more

What are some alternatives?

When comparing teamdeck and Scikit-learn, you can also consider the following products

Hub Planner - Transparent Resource Scheduling, Timesheets, Vacation, Resource Requesting, Project Management & powerful Reports in an agile designed, feasible & intuitive software for simple planning

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

AttendanceBot - Time & attendance tracking for distributed teams

OpenCV - OpenCV is the world's biggest computer vision library

Runn - Runn is a real-time resource management platform with integrated time tracking and forecasting. Intuitively plan projects and schedule resources across the short and long term.

NumPy - NumPy is the fundamental package for scientific computing with Python

Loading...