
Scikit-learn
Pandas
NumPy
OpenCV
Dataiku
Exploratory
WEKA
htm.java
EmbedSocial
Elfsight
Taggbox
Curator.io
Walls.io
Tintup
Juicer
Tagembed
EmbedSocialEmbedSocial is recommended for businesses and individuals who need to showcase user-generated content on their websites, including marketing agencies, e-commerce sites, event organizers, and companies with active social media presence.
Based on our record, Scikit-learn seems to be a lot more popular than EmbedSocial. While we know about 40 links to Scikit-learn, we've tracked only 2 mentions of EmbedSocial. 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.
Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / 3 months ago
Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / 4 months ago
Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 4 months ago
Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 5 months ago
In practice, you’ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 6 months ago
Something along the lines of this: Https://embedsocial.com/. Source: over 3 years ago
Https://embedsocial.com/ is close. Not sure about the monthly grouping though. Source: over 4 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Elfsight - All-in-One platform with 80+ widgets designed to solve any of your website tasks. Customizable Social Feeds, Reviews, Forms, Chats, and many more widgets to increase brand credibility, engage more customers, and skyrocket your sales!
NumPy - NumPy is the fundamental package for scientific computing with Python
Taggbox - Taggbox helps brands in collecting social feeds, reviews, and user-generated content to curate and display them across websites, digital displays, and marketing touchpoints in an engaging and shoppable manner. Helping brands build trust & conversions
OpenCV - OpenCV is the world's biggest computer vision library
Curator.io - Curator is a brandable social media aggregator.