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Based on our record, Scikit-learn should be more popular than Optimage. It has been mentiond 28 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 use the one https://optimage.app/. Source: 11 months ago
Optimage is a batch image compression/resize app that I use to standardise images sent to me by clients for their website. Source: over 1 year ago
I’ve found Optimage to work better, at least for me. Source: over 1 year ago
I have something like this myself setup to automatically optimize new screenshots using Optimage ($15), but I should be able to walk you through the steps, as everything you need is built into Mac. Source: almost 2 years ago
I personally swear by Optimage. Although its primary function is images, it also does video. It is fast and it has a very generous free offering (24 files per day). It doesn't have many options, but to me, that's a feature, not a bug. Source: almost 3 years 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 / 3 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 / 12 months 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
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: over 1 year ago
ImageOptim - Faster web pages and apps.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Caesium Image Compressor - Compress your pictures up to 90% without visible quality loss.
OpenCV - OpenCV is the world's biggest computer vision library
TinyPNG - Make your website faster and save bandwidth. TinyPNG optimizes your PNG images by 50-80% while preserving full transparency!
NumPy - NumPy is the fundamental package for scientific computing with Python