AI models don’t work alone. Behind every prediction is logic — conditions, loops, and decision rules that turn outputs into real actions. Understanding this layer is what separates using AI from building it. #AI #MachineLearning #Python #DataScience
Behind AI Predictions: Logic and Decision Rules
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Just built my own AI agent using Python + Hugging Face 🤖 It’s amazing how combining simple logic with powerful models can turn ideas into real working systems. From handling tasks to generating smart responses, this project showed me how accessible AI development has become. Still improving it every day, but proud of how it’s shaping up 🚀 #AI #Python #HuggingFace #MachineLearning #BuildInPublic #AIProjects
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The Generative AI space can feel overwhelming but the path is simpler than it looks. From Python fundamentals to building scalable GenAI systems, this roadmap breaks it down into actionable steps. The key isn’t learning everything it’s building real, useful systems along the way. Consistency > Complexity. Where are you currently on this roadmap? #GenerativeAI #MachineLearning #DeepLearning #AI #DataScience #LLM #Transformers #RAG #AIEngineering #TechCareers #LearningJourney #Python #Innovation
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Learn chatbot development with Python and Dialogflow in this step-by-step guide, covering benefits, steps, and common challenges of building a conversational AI model https://lnkd.in/gsQd9z2R #ChatbotDevelopmentWithPython Read the full article https://lnkd.in/gsQd9z2R
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day TASK 1- Built a Role-Based AI Chatbot using Python and Ollama with dynamic prompt engineering and conversation memory. Demonstrates how AI responses change based on different roles. #nunnariacademy #aipoweredprogram #ai #freebootcamp #nunnarilabs #generativeai #freebootcamp2026
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Today in our NAVTTC Machine Learning class, we built a chatbot! We used a local LLM model and deployed it using Streamlit. It was really interesting to see how a chatbot works in real time and how we can run AI models locally. What I learned today: • Basics of LLM integration • How to build a simple UI with Streamlit • Real-time chatbot interaction Sharing a small demo of my work Still learning and improving step by step! #NAVTTC #MachineLearning #AI #Chatbot #Streamlit #Python #LearningJourney
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🎬 Following up on my RetailOptim AI post — here is the full live demo. If you missed the slides, check my previous post or the link in comments. 👇 Watch how the tool works end to end in under 3 minutes. #RetailAnalytics #DataScience #FP&A #XGBoost #Python #Streamlit #InventoryOptimization #PricingStrategy #BusinessAnalytics #AI #SupplyChain #SacredHeartUniversity
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The **AI Fundamentals** Bundle 🔍 Course 3 — Understand the Sense of Data Models are only as good as the data fed into them. Encoding, imbalanced data, missing values, outliers, scaling, and splitting. → So you can evaluate, tune, and contribute to AI solutions — not just consume them. #AIFundamentals #GenAI #MachineLearning #DataScience #Python #LearningAndDevelopment #Upskilling #Grokkers
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🚀Day 4 of my AI/ML Journey Today’s focus was on data pre-processing A clear example of the 80/20 rule 💡 — most effort goes into preparing data before building models. Worked on: Handling missing values 🛠️ Scaling features 📊 Visualizing data with heatmaps 📈 Key takeaway: clean and well-prepared data is essential for effective machine learning. #AI #MachineLearning #DataScience #Python #LearningJourney #DataPreprocessing
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🚀 Day 9 of my AI/ML Journey – Making Models Smarter Today, I moved from building models to optimizing them using Hyperparameter Tuning. ⚙️ What I worked on: Implemented Ridge Regression on a real dataset Used GridSearchCV to automatically find the best model parameters Applied Cross-Validation to ensure reliable results Compared performance of default vs optimized models 🔍 I also learned why Cross-Validation is important — it prevents the model from getting “lucky” on a single data split. #AI #MachineLearning #DataScience #Python #HyperparameterTuning
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Built this Number Plate Recognition system using YOLOv8 and OCR and it actually works! The AI detects the plate, isolates it, and reads the number all in real time. Trained the model, tuned the pipeline, and this video is the result of a lot of trial and error. Proud of how it turned out. More projects coming soon. Follow along if you're into AI and computer vision! #AI #YOLOv8 #ComputerVision #MachineLearning #Python #OCR #StudentProject
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