
Scikit-learn
Pandas
NumPy
OpenCV
Dataiku
Exploratory
WEKA
htm.java
Routific
Onfleet
Route4Me
OptimoRoute
Circuit Route Planner
Track-POD
Tookan
WorkWave Route Manager
Scikit-learn
RoutificRoutific is particularly recommended for small to medium-sized businesses involved in delivery operations, including logistics companies, courier services, and any business needing efficient route planning. It is also suitable for companies looking to improve their delivery efficiency and reduce operational costs.
Based on our record, Scikit-learn should be more popular than Routific. 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.
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
Itโs not even better than existing solutions like https://routific.com. Source: about 4 years ago
At work we ended up using something by the name of Routific for it. Let's us split up by time, distance, number of drivers. Worked pretty well but we weren't concerned on pricing since they offered it free for government at the time. Source: almost 5 years ago
There are options that have pricing that are super reasonable for small amounts of routing. https://routific.com/ is an example of one (not that I am recommending it). I saw several others in a Google search. ESRI is another company that probably could get you a decent solution. Source: about 5 years ago
Looking more in to straightaway and routific if by chance anyone has experience with these? Source: over 5 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Onfleet - Onfleet's delivery management software simplifies your local deliveries from start to finish, allowing you to focus more on what really matters.
NumPy - NumPy is the fundamental package for scientific computing with Python
Route4Me - Fleet route planning & route optimization software for SMBs
OpenCV - OpenCV is the world's biggest computer vision library
OptimoRoute - OptimoRoute system helps companies plan efficient routes and schedules for delivery drivers and...