Green Software Foundation’s Post

In today's tech landscape, the environmental impact of software development is gaining attention, with Python often criticized for its relatively high energy consumption. Transitioning from Python to energy-efficient languages like Rust or Go presents an opportunity for businesses to reduce operational costs and carbon emissions. While these languages offer performance advantages, such as lower CPU usage and faster execution times, the decision requires careful consideration of factors like: 1. development time, 2.resource availability, 3. long-term maintenance. Conducting a thorough cost-benefit analysis is essential to assess the financial implications accurately, weighing the upfront investment against potential energy savings and environmental benefits. By prioritizing energy efficiency and sustainability, organizations can make informed decisions that align with both their financial objectives and environmental responsibilities.

After years of interest in the topic of software and the environment, and with my master's thesis giving me the chance to explore it more deeply, I decided to rewrite a part of my theoretical framework as an online article. I believe we're not talking enough about how big the environmental impact of software is, so here are my two cents on making this problem a bit more visible.

"Building a Smarter Energy Meter⚡ with Machine Learning" 😃I'm excited to share a Python program I created to compare machine learning algorithms for classifying energy meter data!  This program can be a valuable tool in identifying different energy consumption patterns, ultimately allowing for optimized energy usage. Here's what the program does: ➣Analyzes data from an energy meter, including voltage, current, power, and classification. ➣Implements and compares the performance of various machine learning algorithms like Logistic Regression, K-Nearest Neighbors, and Decision Trees. ➣Uses stratified K-Fold cross-validation to ensure a robust evaluation of each algorithm's accuracy. ➣Visualizes the results to identify the most effective algorithm for classifying energy consumption patterns. 🔍By identifying the best classification algorithm, we can deploy it directly into smart energy meters. This program has the potential to: ❖Help businesses and households gain insights into their energy usage. ❖Facilitate the development of targeted strategies for energy conservation. ❖Contribute to a more sustainable future through efficient energy management. GitHub link : http://surl.li/srfex #DataScience #MachineLearning #EnergyManagement #energyefficiency #ClassificationAlgorithms #EnergyMeter

💬 Why you can't miss this webinar with Dr. Frank Säuberlich and Dr. Denis Molin, Ph.D, Ing.? ➡️ Energy Sector Challenges: A Deep Dive – Discover how to tackle the most pressing challenges in the energy sector ➡️ The Power Trio: Data, Analytics, and AI in Action – Learn to leverage data, analytics, and AI for transformative solutions ➡️ Envisioning "A Connected Utility" – Explore the concept of "A Connected Utility" – the north star of energy innovation ➡️ Live Demo: Experience a live demo showcasing real-time data preparation and visualization, Python coding at scale, time series analysis on massive energy datasets and much more This will be our first-ever bilingual webinar in English and French. Can't make it live? Sign up anyway, and we'll send you the recorded session!   Register: https://lnkd.in/dWi2Nbiy #Teradata #MachineLearning #AI #DataAnalytics #CloudAnalytics #Sustainability

The paper "Software is Ubiquitous, yet Overlooked" in Nature Computational Science is calling for more attention to software. It insists (or reminds?) the Software Heritage, the software carpentry, the Research Software Alliance, the Hidden Ref, and the Software Sustainability Institute initiatives are the way forward. 👀 https://lnkd.in/eWKYW-U3 #opensource #freesoftware #softwarescience

Register here - https://lnkd.in/daXyJRvc Check live reviews here - https://lnkd.in/de8_bKQa Biology today is fast transforming into data-science - curtsey the high-throughput technologies. Manual analysis of this data is neither feasible nor possible anymore. With the data deluge in Life Science Research, programming is fast becoming a desirable and essential skill, even for wet lab researchers, for data wrangling, analysis, and data visualization. Our goal is to encourage beginners and biologists to learn to code. Coding is simple, intuitive, easy to learn and truly a universal skill today with vast applications in data analysis, data visualization, automation, scaleup and precession. Unleash the power of coding - write your first few of the many codes you may potentially write ... Rediscover yourself !

Register here - https://lnkd.in/daXyJRvc Check live reviews here - https://lnkd.in/de8_bKQa Biology today is fast transforming into data-science - curtsey the high-throughput technologies. Manual analysis of this data is neither feasible nor possible anymore. With the data deluge in Life Science Research, programming is fast becoming a desirable and essential skill, even for wet lab researchers, for data wrangling, analysis, and data visualization. Our goal is to encourage beginners and biologists to learn to code. Coding is simple, intuitive, easy to learn and truly a universal skill today with vast applications in data analysis, data visualization, automation, scaleup and precession. Unleash the power of coding - write your first few of the many codes you may potentially write ... Rediscover yourself !

Register here - https://lnkd.in/daXyJRvc Check live reviews here - https://lnkd.in/de8_bKQa Biology today is fast transforming into data-science - curtsey the high-throughput technologies. Manual analysis of this data is neither feasible nor possible anymore. With the data deluge in Life Science Research, programming is fast becoming a desirable and essential skill, even for wet lab researchers, for data wrangling, analysis, and data visualization. Our goal is to encourage beginners and biologists to learn to code. Coding is simple, intuitive, easy to learn and truly a universal skill today with vast applications in data analysis, data visualization, automation, scaleup and precession. Unleash the power of coding - write your first few of the many codes you may potentially write ... Rediscover yourself !

Register here - https://lnkd.in/daXyJRvc Check live reviews here - https://lnkd.in/de8_bKQa Biology today is fast transforming into data-science - curtsey the high-throughput technologies. Manual analysis of this data is neither feasible nor possible anymore. With the data deluge in Life Science Research, programming is fast becoming a desirable and essential skill, even for wet lab researchers, for data wrangling, analysis, and data visualization. Our goal is to encourage beginners and biologists to learn to code. Coding is simple, intuitive, easy to learn and truly a universal skill today with vast applications in data analysis, data visualization, automation, scaleup and precession. Unleash the power of coding - write your first few of the many codes you may potentially write ... Rediscover yourself