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If everyone agrees that scheduling links help save time, then why are they so universally unloved? Today most booking pages present nothing more than a name and a calendar, so as the person receiving the link, the process of booking a time can feel cold and transactional.
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Based on our record, Scikit-learn should be more popular than zcal. It has been mentiond 29 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.
>ended up just switching over to https://zcal.co and it has been great so far Wait wait wait. It can sync my Google and Outlook calendars into a single scheduling service, and they're not charging me anything? What's the catch here? - Source: Hacker News / over 1 year ago
I've poked around a while ago at some Calendly alternatives (specifically was looking for something that was cheaper than Calendly with most of the basic features). I tried using cal.com for a bit but ended up just switching over to https://zcal.co. All these scheduling apps end up trying to do too much and always seem to end up a bit clunky. - Source: Hacker News / over 1 year ago
There's an even a freer alternative, not FOSS though. http://zcal.co It also allows connection to multiple calendars. - Source: Hacker News / over 1 year ago
Check out zcal.co. Reclaim.ai also works for this as well! Source: over 1 year ago
I usually just use https://zcal.co/ when I need to work out a time slot with some players. Source: almost 2 years ago
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 / 20 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
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Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the 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.
OpenCV - OpenCV is the world's biggest computer vision library
Cron - Cron Calendar.
NumPy - NumPy is the fundamental package for scientific computing with Python