Sense
Brultech GreenEye Monitor (GEM)
Focus
Fido
RescueTime
FocusList
Kinopio
FilePane
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Sense might be a bit more popular than NumPy. We know about 109 links to it since March 2021 and only 107 links to NumPy. 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.
At Sense we make a home energy monitor that provides real-time appliance-level monitoring using machine learning. Hardware is indeed hard as everyone said it would be! https://sense.com. - Source: Hacker News / 10 months ago
If you want to know exactly how much you are using, when, and approximately how much each device is pulling there are sensors that can help. Eg Https://sense.com/ There are a few others. If you are interested I recommend some googling and read reviews. Source: 10 months ago
Hi all, Wondering if you have any other recommendations or thoughts on the below. Use case: I have a solar array and want to track in one spot all the energy produced, energy imported, energy exported, and where energy is being used. Both of the following seem to do what I want with some nuances. I am looking at: 1) Sense [0], which identifies energy use patterns of different devices to determine what devices are... - Source: Hacker News / 10 months ago
Https://sense.com/ try this guy out. I got one and it seems to work fairly well. I have a light fixture that’s wildly inefficient. Source: 11 months ago
I don’t see it mentioned here, but if you really wanted to know what is using power in her whole house, you could get a “Sense” energy monitor. It gets installed by you inside the main breaker panel and lets you see/learns what uses power and allows you to pinpoint large wasters. A little pricey up front, but could easily pay for itself. Source: 12 months ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Brultech GreenEye Monitor (GEM) - - One GreenEye Monitor - Choice of communication option.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Focus - New Tab page that gives you a moment of calm and inspires you to be more productive.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Fido - The safest and most minimalistic smart lock
OpenCV - OpenCV is the world's biggest computer vision library
