Scheduling a meeting shouldn’t require endless rounds of email tag just to find a time that works for all your stakeholders. (“Next month is a no-go, too. Should we try for 3 p.m. CT next year?”)
It’s hard enough to find work-life balance when you’re manually coordinating across time zones and merging details from your work and personal calendars.
You need a stress-free way to manage meetings across all your calendars.
Based on our record, Scikit-learn seems to be a lot more popular than TidyCal. While we know about 29 links to Scikit-learn, we've tracked only 1 mention of TidyCal. 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.
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 / 23 days 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 / 4 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 / about 1 year 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: about 1 year 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: about 1 year ago
We use https://tidycal.com/ because you get a lifetime deal when you buy it and you can sync your calendar with it, so if you or your partners are already booked, it will not allow someone to book during that timeslot. Source: over 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Cal.com - Cal.com (formerly Calendso) is the open source Calendly alternative.
OpenCV - OpenCV is the world's biggest computer vision library
SavvyCal - A scheduling tool both the sender and the recipient will love.
NumPy - NumPy is the fundamental package for scientific computing with Python
Calendly - Say goodbye to phone and email tag for finding the perfect meeting time with Calendly. It's 100% free, super easy to use and you'll love our customer service.