Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
Pl@ntNet
PictureThis
iNaturalist
Garden Answers
Botan: Plant Identifier
Gardenia
HortusFox
Plant Parent
Pandas Pl@ntNetPandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than Pl@ntNet. While we know about 231 links to Pandas, we've tracked only 4 mentions of Pl@ntNet. 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.
Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain aligned. Tools such as Pandas, Spark, or feature platforms such as Feast can be used to implement that logic. - Source: dev.to / 3 months ago
For early-career security practitioners (0-3 years). Start with Python literacy if you do not have it. The free Python Crash Course book and the pandas getting-started guide are enough to bootstrap. Then a hands-on applied course: GTK Cyber's Applied Data Science & AI for Cybersecurity and SANS SEC595 are both reasonable starting points. The goal at this stage is to be able to load a Zeek conn.log into a pandas... - Source: dev.to / 3 months ago
Python and data engineering for security data. Pandas for ingesting Zeek, Sysmon, EDR, and SIEM exports. Timestamp normalization to UTC, join keys across heterogeneous sources, feature extraction from raw logs. Without this layer, the ML content downstream is theater. - 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
Pandas url is the most widely used library for data manipulation. - Source: dev.to / 3 months ago
There are a number of phone apps that will identify trees from a picture. I personally prefer plantnet.org (non-profit entity / no ads or tracking). Source: about 4 years ago
You can also go directly to plantnet.org and perform the same check. Source: over 4 years ago
Get the app from plantnet.org. It's developed by a non-profit consortium of European organizations. I promise it's completely ad free and won't terrorize you in any way. Source: over 4 years ago
You could scrape them off the plantnet.org site. But unless your problem is purely academic you could skip creating your own engine and just use their API. Source: almost 5 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
PictureThis - Instantly identify your plants
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
iNaturalist - iNaturalist is known as one of the most popular nature applications that helps you to identify the animals, plants, insects, and lots of other things with just a single click.
OpenCV - OpenCV is the world's biggest computer vision library
Garden Answers - Garden Answers is an online plant identification application that allows you to get detailed information about any plants or flowers in your garden.