Sense
Brultech GreenEye Monitor (GEM)
Focus
Fido
RescueTime
FocusList
Kinopio
FilePane
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
PandasBased on our record, Pandas should be more popular than Sense. It has been mentiond 198 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.
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
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 14 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 7 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Brultech GreenEye Monitor (GEM) - - One GreenEye Monitor - Choice of communication option.
NumPy - NumPy is the fundamental package for scientific computing with 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
