iExec
Chainlink
Polkadot
Wanchain
Truebit
Cartesi
Polygon (Matic)
Band Protocol
Scikit-learn
Pandas
NumPy
OpenCV
Dataiku
Exploratory
WEKA
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iExec Scikit-learnBased on our record, Scikit-learn should be more popular than iExec. It has been mentiond 40 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.
Ontochain projects have not yet begun to use the sidechain, but they should be very soon. The oracle factory upgrade from the beta version, should also give much more usage to the iexec marketplace. You can find current usage at :https://iex.ec/ . Source: almost 4 years ago
Let us know what you think: https://iex.ec. Source: about 4 years ago
iExec (RLC) claims to have developed the first decentralized marketplace for cloud computing resources. Blockchain technology is used to organize a market network where users can monetize their computing power, applications, and datasets. By providing on-demand access to cloud computing resources, iExec is reportedly able to support compute-intensive applications in fields such as AI, big data, healthcare,... Source: about 4 years ago
There are also lots of compute networks, that compete with cloud offerings of AWS, and google cloud and microsoft. Like Golem, pp.io, iex.ec, etc. Source: over 4 years ago
It's the explorer listed on iexec's website https://iex.ec/. Kinda alarming if a person wanted to setup an account with them to have a worker earn RLC. Looks like they wouldn't even be able to and it's been down for hours. Source: almost 5 years ago
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 / 3 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 / 3 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 / 4 months ago
In practice, youโll 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
Chainlink - Chainlink Marketing Platform provides advanced marketing automation,ย business intelligence, and attribution across all channels.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Polkadot - Polkadot is a Web3 decentralized cross-blockchain protocol that seeks to connect different blockchains, enabling them to share security, interoperate and transact with each other.
NumPy - NumPy is the fundamental package for scientific computing with Python
Wanchain - Wanchain is a blockchain platform that enables the transfer of value between different blockchains.
OpenCV - OpenCV is the world's biggest computer vision library
