I built an Unbeatable Tic Tac Toe AI using Python and the Minimax algorithm with Alpha-Beta Pruning. The AI never loses—only wins or draws. 👉 Live Demo:https://lnkd.in/gyi4fs_p #Python #AI #GameAI #Streamlit #Projects

Temporal.io is emerging as a top choice for building reliable agentic workflows in production. I've been working through their AI cookbook examples and putting together a reference repo as I go: https://lnkd.in/gnwP-a6k #Temporal #TemporalIO #AgenticAI #AIAgents #Python #LLM #WorkflowAutomation

What is smolagents? smolagents is an open-source Python library designed to make it extremely easy to build and run agents using just a few lines of code. https://lnkd.in/d2ukC5aR #Agents #AIAgents #Smolagents #HF #AngeloSorte #2026 #AI #AIEngineering

🐍 Day 67 — Correlation Heatmaps Day 67 of #python365ai 🔥 Heatmaps visualise correlation between variables. Example: sns.heatmap(df.corr()) 📌 Why this matters: Correlation analysis is key in feature selection. 📘 Practice task: Generate a correlation matrix and visualise it. #python365ai #Heatmap #FeatureEngineering #Python

Built my own RAG (Retrieval-Augmented Generation) system from scratch using Python Worked on the complete pipeline: Extracting text from PDF Splitting into meaningful chunks Creating embeddings using Ollama Storing data in Chroma vector database Retrieving relevant information using similarity search Next step is to integrate an LLM and turn this into a full AI-powered application 💡 #AI #MachineLearning #Python #RAG #Ollama #BuildInPublic

Recently I attended a webinar on Python 🐍 with AI 🧠 by TOPS Technologies 🧑💻 . Honestly, it was a really interesting session 👌. 👉 I got to understand how Python is actually used in AI and real-world applications. ✍ Still learning, but moving step by step 👍 #Python #AI #LearningJourney

Recently started exploring Python in the AI ecosystem. One thing I really like about Python is how quickly you can move from idea to implementation. Example: A simple model predicting output from input data. from sklearn.linear_model import LinearRegression X = [[1], [2], [3]] y = [2, 4, 6] model = LinearRegression() model.fit(X, y) print(model.predict([[4]])) Just a small experiment, but it shows how machines can learn relationships from data. Excited to keep learning and building more with Python and AI. #Python #AI #MachineLearning #DeveloperLife

🐍 Day 62 — Scatter Plots Day 62 of #python365ai 🎯 Scatter plots reveal relationships between variables. Example: plt.scatter([1,2,3], [2,4,5]) plt.show() 📌 Why this matters: Scatter plots are foundational in regression analysis and ML. 📘 Practice task: Plot two related numeric lists. #python365ai #ScatterPlot #MachineLearning #Python

CodSoft Tasks Built a Movie Recommendation System using Machine Learning & Python This project uses: ✅ TF-IDF Vectorization ✅ Cosine Similarity ✅ Content-Based Filtering ✅ Tkinter GUI for user interaction The system analyzes movie descriptions and recommends similar movies based on textual similarity. Tech Stack: Python Pandas Scikit-learn Tkinter Projects like this help me understand how platforms like Netflix recommend content 🎯 #MachineLearning #Python #RecommendationSystem #DataScience #AI #ProjectBasedLearning

Demo Video: YouTube Chatbot using RAG & LLMs Primary Post: https://lnkd.in/g4uFVXRc Code: https://lnkd.in/gehUmsXZ Nitish Singh CampusX #AI #GenerativeAI #LLM #RAG #Python #MachineLearning #CampusX