Based on our record, Scikit-learn should be more popular than LucidChart. 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.
I'm thinking something like a lucidchart.com set up, but also wondering since one project is complete if there is anything that can just analyze an existing codebase and automatically do the work for me. Source: over 3 years ago
Oh! excalidraw.com is great for quick paper style diagrams. I have used it a fair bit. The roam integration is good. But I always revert back to draw.io because it's open sourced, simple to use and just works :D If you are looking for more, a paid option would be lucidchart.com. Source: over 3 years ago
You could try lucidchart.com or draw.io. I have used both. Source: about 4 years ago
Otherwise, you may be thinking about a "mind-map" of sorts... Simply to show relationships? Diagrams.net, lucidchart.com. Source: about 4 years ago
What is difference between Yours tool and others like arcentry.com lucidchart.com cloudcraft.co hava.io ? Would be nice to support diagrams as code ( generated from kubernetes states, terraform, pulumi, etc..) Personally I dont think that another diagram tool can beat ^ platforms. Source: about 4 years ago
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 / 4 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 6 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 / 12 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 / over 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
draw.io - Online diagramming application
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
yEd - yEd is a free desktop application to quickly create, import, edit, and automatically arrange diagrams. It runs on Windows, Mac OS X, and Unix/Linux.
OpenCV - OpenCV is the world's biggest computer vision library
OmniGraffle - OmniGraffle is for creating precise graphics like website wireframes, an electrical system designs, or mapping out software class.
NumPy - NumPy is the fundamental package for scientific computing with Python