Python in Aging Research: Unlocking Lifespan Insights

I recently had the opportunity to participate in the IEEE Region 4 Nexus event, where I presented my work on machine learning–based anomaly detection. In this project, I focused on identifying fraudulent transactions in highly imbalanced datasets using the Isolation Forest algorithm. The study highlights challenges such as class imbalance and model evaluation using metrics like Precision, Recall, ROC-AUC and PR-AUC. #IEEE #MachineLearning #DataScience #AnomalyDetection #Python

The exploration of aging is increasingly accessible, particularly through the utilization of Python. Researchers are employing advanced algorithms and data analysis techniques to uncover the complexities associated with lifespan and the potential pursuit of immortality. By leveraging the capabilities of Python, we can effectively model aging processes, analyze extensive biological datasets, and investigate interventions that may ultimately extend human longevity. This endeavor not only enhances our comprehension of the science of aging but also paves the way for novel pathways in biomedical research. Read more at https://lnkd.in/ea98rhXj. #AgingResearch #Python #DataAnalysis #BiomedicalResearch #Longevity

atomcamp AI bootcamp Weekend Update: It is said that teaching is the best way to learn. Over the weekend I had the opportunity to host sessions on the following topics: 1. Introduction to Python where we discussed the basic syntax of Python. The data structures in Vanilla Python, their benefits and limitations, and how NumPy solves the problem of numerical computation in Python. Muhammad Zuraiz Amir had some very interesting questions that made the session more exploratory and informative. 2. Prompt Engineering where we discussed the basic anatomy of a prompt, how the behavior of LLMs and Generative AI (Gen AI) can be customized with the prompt, elements of a good prompt. We also had a fruitful discussion about the advantages and disadvantages of online and offline LLMs . Thank you Fazal E Subhan for your curiosity and interest. #AI #Atomcamp #Bootcamp #Python #PromptEngineering #LLM #GenAI

📊 Permutation & Combination in Data Analysis using Python Today, I explored the concepts of Permutation and Combination and applied them in data analysis using Python. Understanding these statistical techniques helps in solving problems related to arrangement, selection, and probability. By using Python, I was able to efficiently implement these concepts for analyzing different data scenarios and improving problem-solving skills. This practice enhanced my knowledge in combinatorics and its real-world application in data analysis and decision-making. Continuing my journey in learning advanced data concepts and applying them practically! 🚀 #DataAnalysis #Python #Statistics #Permutation #Combination #Combinatorics #DataScience #ProblemSolving #LearningJourney #DataAnalytics

Recently completed training in optimization using Python, focusing on mathematical modeling and computational problem solving. A simple example from mathematics illustrates this well. Given 100 meters of fencing used to form three sides of a rectangular garden along a wall:2x + y = 100 Maximize the area: A = x · y Using calculus, the optimal solution is straightforward: x = 25, y = 50 → maximum area = 1250 However, the same problem can also be approached from an optimization perspective. Instead of solving analytically, the problem can be formulated by defining decision variables, constraints, and an objective function, and then solved computationally. The constraint is modeled as an equality (2x + y = 100), since the maximum area is achieved when all available fencing is fully used. While this is a simple example, the same approach extends directly to more complex problems in logistics, pricing, and resource allocation. It is a useful reminder that many real-world optimization problems are solved not through closed-form solutions, but through structured modeling and computational methods. #OperationsResearch #Optimization #Python #Mathematics #DataScience Here is a simple implementation in Python:

I just built a small Python project today to simulate how a population of cells grows over time. At the start it grows fast, then it slows down and levels off once it reaches a limit, due to limited resources (eg. lack of nutrients, environmental factors). This is the first time I’ve actually built something like this on my own instead of just following along tutorials, so it was a bit messy but I learned a lot from it. I find it really interesting to see how a simple model can represent something real in biology. Code at: https://lnkd.in/gPwjx8Sz #Python #Biology #DataScience #MachineLearning #MathematicalModelling #Coding

The weekend is approaching and what better idea than setting up your computer for a "Learn how to code" date? Check out the learning portal on Proteintech Group website and discover all the free courses available. Introduction to Python for Biologists is the latest released. In this extensive beginner course, you will learn the basics of Python, from loops and conditions to data analysis. And you will also learn how to apply Python to your own research, for example in experiments like Western blot quantification, ELISA, qPCR analysis and protein structure exploration. All courses on the Learning Portal are free and you can complete them at your own pace. Follow the link to try out: https://lnkd.in/dSw9wn3q #Discoverwithproteintech #coding #python

There are many different students in today's classrooms with many different abilities. And AI tools can make a big difference in their learning experiences. In this guide, Omotayo walks you through building a Speech-to-Text & Text-to-Speech accessibility tool in Python. https://lnkd.in/gqyk9eeU

Data Analysis and Machine Learning with Python and R This course is designed for PhD scholars, research students, and freelancers from any field of study. #datascience #machinelearning #dataanalysis #python #AITraining

Learn the fundamentals of NumPy in Python with this beginner-friendly introduction! 🚀 In this video, I’ve covered: What is NumPy? Why NumPy is important NumPy arrays basics Difference between lists and arrays Basic operations in NumPy NumPy is one of the most powerful libraries in Python for numerical computing and is widely used in Data Science, Machine Learning, and AI. See the Details Video here : https://lnkd.in/d4ShsbXj 💡 If you are starting your journey in Python or AI, this video will help you build a strong foundation. #NumPy #Python #PythonForBeginners #LearnPython #DataScience #MachineLearning #AI #Coding #Programming #PythonTutorial #Developers #Tech #ArtificialIntelligence #DataAnalysis