Keith McNulty’s Post

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Unveiling the Intricacies of Gradient Descent Through a Technical Lens Gradient descent isn't merely an optimization algorithm—it's a profound journey through a landscape marked by complexity and precision within the realm of machine learning. Today, I'm excited to share a deeper dive with a technical visualization that distinctly highlights the algorithm's trajectory across a multi-dimensional loss surface. Deep Dive into the Mechanics: The accompanying graph vividly displays a complex function characterized by multiple minima and maxima. Through gradient descent, we navigate this challenging terrain in search of the elusive global minimum. I've annotated key points along the descent path to illustrate how gradients are calculated and parameters are methodically updated at each step. This exploration not only enhances our understanding of gradient descent but also underscores its crucial role in optimizing machine learning models. Stay tuned for more insights as we continue to uncover the technical subtleties of AI and machine learning methodologies. Python Code: def gradient_descent(gradient, start, learn_rate, n_iter=50, tolerance=1e-06):   vector = start   for _ in range(n_iter):     diff = -learn_rate * gradient(vector)     if np.all(np.abs(diff) < tolerance):       break     vector += diff   return vector # Example usage gradient = lambda v: 2*v # Gradient of f(v) = v^2 start_point = np.array([10.0]) learn_rate = 0.1 min_point = gradient_descent(gradient, start_point, learn_rate) print("Minimum point of the function:", min_point) This implementation demonstrates the algorithm's potential to tackle even the most intricate functions, making it a cornerstone of machine learning efficiency. #MachineLearning #DataScience #AI #TechVisualization #PythonCode #GradientDescent

Have you ever pondered the method by which scientists and researchers arrive at unwavering conclusions drawn from an array of data? The enigma behind this process lies in the art of hypothesis testing, an indispensable tool that empowers us to substantiate our assumptions and derive meaningful insights from the evidence at hand. In this document, we embark on a journey to unravel the intricacies of hypothesis testing, demystifying the steps and principles that guide this scientific practice. Prepare to unlock the extraordinary potential of data-driven decision-making and witness how hypothesis testing serves as the linchpin of evidence-based discovery. 🛎 Become a part of our vibrant AI community. Check out the link in the comments below. #datascience #datasciencejobs #datasciencetraining #datascienceeducation #datasciencecourse #python #pythonprojects #data #dataanalysis #dataanalytics #datascientist #machinelearning #artificialintelligence #ai #deeplearning #machinelearningprojects #datascienceprojects

Hey, everyone! 👋  Sharing a recent project milestone from my journey at #OasisInfobyte! In Task 1, I tackled the evergreen Iris dataset, implementing Decision Trees. The result? A solid 98% accuracy in predicting iris species. Not bad for predicting which flower is fancier than the others, right?  Here's the scoop: 📦 Data Collection: Utilized Python and Seaborn for dataset handling. 🌿 Feature Engineering: Splitting data into training and testing sets for accuracy assessment. 🌳 Decision Tree Model: Employed Decision Tree Classifier with post-pruning techniques. 🖼️ Visualizing the Decision Tree: Visualized the decision-making process. 🔮 Predictions and Evaluation: Achieved an impressive 98% accuracy on test data. 📊 Classification Report: A closer look at precision, recall, and F1-score. Kudos to #OasisInfobyte for fostering innovation in AI and data science. Excited to dive deeper into the AI realm! #IrisClassification

Last week, Mario Rodríguez Ibáñez got to share his thoughts on the future of data and AI with EM360Tech at #CDAOUK 🤖 He and Andy Wisbey had great conversations about Dash Enterprise with data analytics leaders – thank you to everyone we had the pleasure of connecting with! Hear what Mario thinks about the following:  • What data leaders need to prepare to get the full benefits of generative AI • Where AI implementation could take data companies in 2024 • How Plotly simplifies your data analysis and app development Watch the full interview ➡️ https://lnkd.in/edGChrx3

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What Do Data Scientists Do? 🤔 A Brief Guide to AI Maturity, Challenges, and Solutions🔝🔝🔝 #datascience #datascientists #datascientist #ai #artificialintelligence #machinelearning #ml #aimodelling #analytics #dataanalytics #pythonprogramming #python #r #aijobs #datasciencejobs #aiengineering https://lnkd.in/dugp2JnZ

My brain is buzzing after week 3 of data analysis & machine learning! 🤯 💡 This week in my AISOCIETY journey, we've been breaking down complex concepts: 🌳 Decision Trees, Naive Bayes, Linear & Logistic Regression – Explained in plain English with real-world examples to build that 'aha!' understanding. 🤖 Support Vector Machines, Neural Networks, and the mysterious Kernel Trick – These advanced techniques are starting to make sense! 🔍 K-means, Hierarchical Clustering, and more – Mastering the fundamentals of model building. 📈 Diving into model evaluation with Confusion Matrix, Accuracy, F1 scores...all those metrics that make sure our models actually work! 🤯 Overfitting, underfitting... wrapping my head around how to build models that truly generalize. 📝 Quizzes galore! Keeps me on my toes and solidifies those concepts. I'm obsessed with how Support Vector Machines can find the perfect dividing line between data points – it feels like magic! ✨ Can't wait to put these skills into practice! Stay tuned for projects and more insights. 🚀💻 #DataAnalysis #MachineLearning #Python #AISOCIETY #DecisionTrees #NaiveBayes #LogisticRegression #SupportVectorMachines #NeuralNetworks #KMeans #HierarchicalClustering #ModelEvaluation #LifelongLearning

𝐓𝐡𝐞 𝐯𝐨𝐭𝐞𝐬 𝐚𝐫𝐞 𝐢𝐧! 🌟 And the final name for our 30-day online challenge is... ☞ 𝟑𝟎𝐃𝐚𝐲𝐬𝐀𝐈𝐀𝐬𝐜𝐞𝐧𝐬𝐢𝐨𝐧! We're all set to embark on this transformative journey, and I can't wait to share all the incredible content I've prepared for you. From transformers to generative AI, we'll cover it all! 🗓 Save the Date: The challenge starts on October 23, 2023. Don't miss out! 👀 Keep an eye out for the final flyer with all the details. Can't wait to see you there! 🔔 Stay Updated: Subscribe to my newsletter for exclusive updates and insights: https://lnkd.in/digSjNcC Don't forget to subscribe to my YouTube channel and hit the bell icon to get notified whenever a new video is uploaded! https://lnkd.in/gW37c4VY ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬  I share ML/ Data Science/ AI content on a regular with my LinkedIn family. Follow Zoumana KEITA, and activate the 🔔 under my profile! #AI #Technology #MachineLearning #LargeLanguageModels #AIChallenge #Transformers #GenerativeAI #LearningJourney #TechChallenge #DataScience #Community #Tech #Programming #Python #DataScientist