LeetCode
HackerRank
Project Euler
Codewars
CodeForces
Exercism
interviewing.io
Coderbyte
Scikit Image
OpenCV
Microsoft Computer Vision API
Amazon Rekognition
Microsoft Video API
Clarifai
SimpleCV
Cloudinary
LeetCode
Scikit ImageLeetCode is the best platform to help people practice solving coding problems and prepare for technical interviews. The main users are software engineers. LeetCode has over 1,900 questions covering many different programming concepts.
Based on our record, LeetCode seems to be a lot more popular than Scikit Image. While we know about 543 links to LeetCode, we've tracked only 7 mentions of Scikit Image. 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.
Category Tool URL How I used it General AI assistant ChatGPT Https://chatgpt.com Breaking down concepts, simulating interviewers, reviewing answers AI writing / reasoning Claude Https://claude.ai Refining behavioral stories and system design explanations Coding practice LeetCode Https://leetcode.com Core DSA practice and timed coding drills Coding explanations NeetCode Https://neetcode.io Pattern-based... - Source: dev.to / about 2 months ago
Plain BST. Fine when input is random or the problem doesn't require worst-case guarantees. Tree problems on LeetCode typically assume balanced input and don't ask you to maintain balance yourself. - Source: dev.to / 2 months ago
Your preparation should not be random. Platforms like LeetCode, Codeforces, and GeeksforGeeks are toolsโbut what matters is how you use them. - Source: dev.to / 3 months ago
Bash /path/to/chrome-launcher.sh email001@gmail.com https://leetcode.com. - Source: dev.to / 3 months ago
AI-Powered Learning Tools: Consider using AI-driven platforms like Khan Academy or LeetCode that can personalize your learning experience based on your progress and skill level. - Source: dev.to / 10 months ago
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics. - Source: dev.to / about 2 years ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / over 2 years ago
This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/. Source: over 3 years ago
Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/. Source: almost 4 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 4 years ago
HackerRank - HackerRank is a platform that allows companies to conduct interviews remotely to hire developers and for technical assessment purposes.
OpenCV - OpenCV is the world's biggest computer vision library
Project Euler - Project Euler is a series of challenging mathematical/computer programming problems that will...
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Codewars - Achieve code mastery through challenge.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.