Ganttic VS NumPy
Compare Ganttic VS NumPy and see what are their differences
Employee Monitoring Software with Screenshots, Internet, Activity and Time Tracking
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Ganttic
ResourceGuru
Float
When I Work
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Sling
Shiftee
eResource Scheduler
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
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With a real-time overview of your organization's resources, projects, and tasks, Ganttic simplifies resource scheduling and management. Visual Gantt charts help you to not only allocate resource quickly, but check in on the progress of your projects. While features such as drag and drop scheduling make it easy to update plans smoothly and on-the-go.
With Ganttic you can make a clear plan of action for your projects and their capacity planning. Plus, built in metrics such as utilization tracking ensures you're getting the best efficiency from your team. Create plans from the POV of resources or projects, switching at anytime for new insights.
All this plus automated reports, unlimited sharing and users, and world-class customer support make Ganttic the perfect planner for your resource planning. For the past 10 years Ganttic has been serving clients from every industry and in every corner of the world. Start with a free trial and see why!
GantticGanttic's answer
Ganttic is for managers unsatisfied with their one-size-fits-all software, and anyone who is looking for something more customizable, flexible and personalized.
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 / 8 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 / 9 months ago
The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
ResourceGuru - The fast, simple way to schedule people, equipment, and other resources online.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Float - The leading resource management software for agencies, studios, and firms. With a simple, drag and drop interface and powerful editing tools, Float saves you time and keeps projects on track.
OpenCV - OpenCV is the world's biggest computer vision library
When I Work - When I Work is an employee scheduling and communication app using the web, mobile apps, text messaging, social media, and email.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.