Based on our record, Scikit-learn should be more popular than Geekbot. It has been mentiond 31 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.
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
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months 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 / 11 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 / about 1 year 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 / almost 2 years ago
We think GitReport could replace standup apps like Geekbot. So we're making it into a product. More Git features are coming, like tracking issues and pull requests. Source: over 1 year ago
We run standups every day, however only 2x of them are a Teams call. The other 3 are run using a tool called Geekbot (Yes scrum masters do hate this) which is basically just a chatbot that sends you the standard standup questions and you can answer whenever you feel like it. This has helped our team heaps due to having such a huge mix of people in our team (Cloud Eng, Database Eng, Software Eng, Network Eng) that... Source: almost 2 years ago
My new job recently pulled in https://geekbot.com/ to handle stand ups. Answer a couple basic questions when you login, and they’re all sent to a central channel. I’m not big on that type of communication in general, but it takes maybe 30 seconds each morning. Source: about 2 years ago
We use Geekbot to help standups. The feedback from each dev goes into a channel, then we talk about things that need to be addressed or things we're working on. Source: over 2 years ago
Back in 2005, I remember working on startups running on Scrum principles. It worked well at the time, we where able to ship, grow the team, and move forward with a nice few-features-per-week cadence, working remotely, on a small team; less than 10. Tt always worked fine, but very slow, as all-dev-things were at the time. I worked with ActiveColab in 2007, Skype 2007, Yammer 2009, Trello 2011, Pivotal Tracker 2013,... - Source: Hacker News / over 2 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Standuply - Run daily standup meetings and track your metrics in Slack
OpenCV - OpenCV is the world's biggest computer vision library
Chili Piper - Chili Piper is an intelligent calendar for Sales teams, to book their own meetings or set appointments for other teams.
NumPy - NumPy is the fundamental package for scientific computing with Python
Doodle - Make meetings happen. With Doodle, scheduling becomes quick and easy.