
CoinEx
SwapSpace
Mushino
sIFR
Bybit
Omgfin Exchange
SimpleSwap.io
InstaSwap
Scikit-learn
Pandas
NumPy
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Dataiku
Exploratory
WEKA
htm.java
CoinEx
Scikit-learnbut the last week or so they have been kind of shady in my opinion. Ive never had an issue with trading before 9-8-21 and when I needed customer service they would always be quick to respond and resolve. They have been adding new tokens which is great. Kinda copy adding whatever coinbasebase adds and then some. Since that date "service unavailable" issues have started popping up. I don't know if it's to prevent sell offs when prices start to dip but it coincides with it. They did support FTM mainnet withdrawals but suspended them saying "wallet maintenance" but still accepts deposits from mainnet. I believe it's to force the ERC20 FTM on users so we withdraw and they reap the Benefits of charging the withdrawal fees while we end up paying withdrawal fees and eth gas fees to bridge over to mainnet and no hastle for them. Lastly, there is a trading contest for most net trading value. I wasn't just buy and sell buy and sell causing chaos and neither was anyone else from what I seen. After trading all week using 150-175 dollars worth of tokens I manage to get to the top 3 and eventually first. 46000 worth of trading value. Now there are 4 huge orders, 2 buy and 2 sell that make it impossible to do anything, that popped up after out of nowhere taking 1st and 2nd. I only sell if it's a 7 dollar profit so it covers the trading fees and I don't lose anything. To do that and be able to move up in the competition, I now need to have $2500-$6000 just to have a chance of the price going up to my ask price. Or $2500-$6000 to be able to place a buy order low enough to not lose money. Could be coincidence and it's 2-3 actual users trying to defend their spots. Just be aware.
CoinEx might be a bit more popular than Scikit-learn. We know about 48 links to it since March 2021 and only 40 links to Scikit-learn. 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.
If you want to use a centralised exchange, check out: Https://xgo.com/ Https://coinex.com/ Https://mercatox.com/ (available in USA afaik). Source: about 3 years ago
My friends from the US had no issues using coinex.com. Source: over 3 years ago
Coinex I find has better liquidity for Ergo than Kucoin. I would avoid making large purchases on Kucoin. Source: over 3 years ago
Coinex.com and hitbtc.com still seem to have their BSV nodes in sync. Source: over 3 years ago
I'm on coinex.com, which requires separate authentication and approval for each withdrawal, like phone + email (ie. 2FA). Source: over 3 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 / about 2 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 / 2 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 / 3 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 / 5 months ago
SwapSpace - SwapSpace is a cryptocurrency aggregator exchanger.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Mushino - The easiest place to go long or short on cryptocurrencies
NumPy - NumPy is the fundamental package for scientific computing with Python
sIFR - sIFR is a JavaScript and Adobe Flash dynamic web fonts implementation, enabling the replacement of text elements with Flash equivalents.
OpenCV - OpenCV is the world's biggest computer vision library