Gumlet Video streamlines the process of uploading, transcoding, optimizing, hosting, and analyzing videos, enabling rapid streaming to vast audiences. Gumlet Image Optimization enhances website speed, responsiveness, user experience (UX), and search engine optimization (SEO).
Gumlet is loved by 8000+ businesses and start-ups and delivers over 1.5 Billion media files daily. With an average optimization rate of 54%, Gumlet offers an exceptional video and media experience for users across websites and applications.
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Image loads fast, im impressed with the speed and ease of installation. I have successfully deployed them on afew of my websites and it improves my overall loading speed.
Gumlet is a wonderful little tool that I use for optimising your images and thus your website loading speeds. We use it for our work (and client projects) and it works very well!
Pros: - Inbuilt CDN - Easy integration with Wordpress - on-the-fly image manipulation is awesome - Supports CNAME now!
Cons: - Missing some smart (AI-like) image manipulation features that Cloudinary has like Smart/Face-cropping for example. Would love to have those!
Gumlet is easy to implement and instantly improves the performance of your site. I compared to other providers and was happy to see that it outperforms the competition
Based on our record, Scikit-learn seems to be more popular. 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.
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 Aurรฉlien Gรฉron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 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 / 11 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: 12 months 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: about 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Cloudimage - Cloudimage.io is the easiest way to resize, store, and deliver your images to your customers through a rocket fast CDN.
OpenCV - OpenCV is the world's biggest computer vision library
ImageKit.io - Instant multi-platform image optimization
NumPy - NumPy is the fundamental package for scientific computing with Python
Cloudinary - Cloudinary is a cloud-based service for hosting videos and images designed specifically with the needs of web and mobile developers in mind.