Steven Hedges’ Post

🚀 Built an ANN for Regression I recently developed an Artificial Neural Network to tackle a regression problem. With optimized layers and hyperparameters. 🔍 Tech Stack: Python, TensorFlow, Colab 📊 See the Notebook: https://lnkd.in/g9KACMjP Have you tried ANNs for regression? Let’s connect and share insights! #MachineLearning #NeuralNetworks #Regression #AI

Lectures 10, 11, and 12 Highlights: Advanced AI with Sir Irfan Malik As-salamu alaykum! Today, in our Advanced AI Learning Journey, we are covering three essential lectures with Sir Irfan Malik. In these sessions, we will discuss: - Conditional statements - Loops (while loops and for loops) - User-defined functions in Python - Open Ai To enhance your learning experience, we've prepared a Colab notebook with practical exercises. Check out the link below and follow along with the exercises. 📚 Colab Notebook Link of Lecture 10 https://lnkd.in/d_fNBGFy 📚 Colab Notebook Link of Lecture 11 https://lnkd.in/dA67vN-P 📚 Colab Notebook Link of Lecture 12 https://lnkd.in/dEfsjd5v Let's continue building our Python skills together! #AI #Python #Functions #Loops #ConditionalStatements #LearningJourney #ZeonSolutions #TechSkills #ContinuousLearning

If you're like me and sometimes run into GPU limitations on your local machine, I Tried a neat workaround to run Ollama in Google Colab, allowing you to leverage Colab's resources for your AI projects. You can find how To set it up Here : https://lnkd.in/deU6-HHY #GenerativeAI #LLM #RAGsystems #ArtificialIntelligence #MachineLearning #DataScience #AIResearch #TechInsights #AIApplications #AICommunity #Ollama #Python

It was claimed on this forum that Large Language Models will not solve optimization problems "any time soon" (see thread: https://lnkd.in/eBJXufdF). I guess they won't if nobody asks them to. But, since I'm paying the $200 anyway, and since Steve Moffitt if no-one else was interested, I might as well get this little research project started with this prompt: "Take all the methods in HumpDay at https://lnkd.in/gr6shcD and understand the ideas in them. Then devise a new heuristic derivative-free optimization procedure that combines some ideas. Then benchmark it in Python." Here is the result: https://lnkd.in/eDnttCr5 self-described as "A toy meta-heuristic that adaptively selects among sub-optimizers". The code runs first time. I'm not suggesting this is publishable research, or even logical, just that somebody might have fun running with this one given that that there are reasonably straightforward ways of evaluating the thousands of candidate algorithms that can be generated in this manner. If you do co-invent something sneaky, I'd love to accept your pull request: https://lnkd.in/eAm-V2qt #llms #optimization https://lnkd.in/eDnttCr5

https://lnkd.in/dDsV4ikQ A code that Predict sales prices and practice feature engineering, RFs, and gradient boosting. #Python #Machinelearning

🚀 Exploring Non-Euclidean Clustering Algorithms! 🌐 Excited to share my latest project on clustering in non-Euclidean spaces using spherical and hyperbolic distance metrics. Dive into the code and visualizations to see how we can push the boundaries of traditional clustering methods. Check it out on Colab: https://lnkd.in/gY-D6YF3 #DataScience #MachineLearning #Clustering #NonEuclidean #AI #Python

🚀 Getting Started with K-Nearest Neighbors (KNN) in Python 🤖 Check out my implementation of the KNN classification algorithm using Python! In this project, I worked on classifying users based on their age and estimated salary. The process involved: ✅ Loading and exploring the dataset using Pandas and NumPy. ✅ Preprocessing the data with train_test_split for splitting and StandardScaler for feature scaling. ✅ Building the KNN model using KNeighborsClassifier from Scikit-learn. ✅ Testing and predicting results to gain valuable insights. 📌 Code Highlights: Feature scaling ensures uniformity for better predictions. minkowski metric with p=2 for Euclidean distance. and K=5 Achieved predictions that can help businesses make data-driven decisions! 🔑 Key Takeaway: KNN is a powerful yet simple algorithm for classification tasks and is highly effective when working with smaller datasets. link==>>(https://lnkd.in/e-JW_RjC) #MachineLearning #Python #DataScience #KNN #AI #DataAnalysis #Coding

Check on my Cat and Dog Image classifier using TensorFlow (Machine Learning with Python)

Hello Connections! 😊 Today, I am excited to share the completion of my latest project in the AI field: YouTube Analysis Using Python. 📊🔍 In this project, I delved deep into YouTube's data, leveraging advanced data analytics to uncover key insights and trends through real-time data scraping and analysis. Here’s a glimpse of what I have accomplished: https://lnkd.in/dJipG6Dj #DataScience #MachineLearning #Python #YouTubeAnalytics #AI #trending #ArtificialIntelligence

https://lnkd.in/d8Ct2BcE A code that predicts the bikes sharing count using machine learning and deep learning. #Python #Machinelearning #Deeplearning