akshatanand-cell/CODSOFT

markdown ## 🗂️ Project Index | # | Task | Technology | Status | |---|------|------------|--------| | 01 | 🤖 [Rule-Based Chatbot](#-task-1---rule-based-chatbot) | Python, RegEx, Streamlit | ✅ Completed | | 02 | ♟️ [Tic-Tac-Toe AI](#️-task-2---tic-tac-toe-ai) | Python, Minimax, Streamlit | ✅ Completed | | 03 | 🖼️ [Image Captioning](#️-task-3---image-captioning) | BLIP, PyTorch, Transformers | ✅ Completed | | 04 | 🎬 [Recommendation System](#-task-4---recommendation-system) | TF-IDF, Scikit-learn, Pandas | ✅ Completed | | 05 | 👁️ [Face Detection](#️-task-5---face-detection) | OpenCV, Haar Cascade, CV | ✅ Completed | ## 🤖 Task 1 - Rule-Based Chatbot ### 📌 Overview A smart rule-based chatbot that understands user inputs using **regex pattern matching** and responds with predefined intelligent responses. ### ✨ Highlights - 🎯 20+ conversation topics covered - 💬 Greetings, jokes, AI knowledge, time & date - 😊 Emotion detection & response - 🎨 Beautiful animated purple UI - ⚡ Instant responses — no API needed ### 🛠️ Tech Stack Language: Python 3.11 Framework: Streamlit AI Method: RegEx Pattern Matching Libraries: re, random, datetime ### 💬 Sample Chat You → "Hello!" Bot → "Hey there! What can I do for you?" You → "Tell me a joke" Bot → "Why did the AI go to school? To improve its neural network! 😄" You → "Who made you?" Bot → "Akshat Anand — CodSoft AI Intern 2026! 🚀" ## ♟️ Task 2 - Tic-Tac-Toe AI ### 📌 Overview An **unbeatable AI** that plays Tic-Tac-Toe using the **Minimax algorithm** — it evaluates every possible move and always picks the best one. ### ✨ Highlights - 🧠 Minimax algorithm — AI never loses - 📊 Live score tracking (Win/Draw/Loss) - 🎨 Color coded board (X=Blue, O=Red) - 🔄 New game button - ⚡ Instant AI response ### 🛠️ Tech Stack Language: Python 3.11 Framework: Streamlit Algorithm: Minimax (Game Theory) Complexity: O(9!) worst case ### 🎮 How Minimax Works AI evaluates ALL possible moves ⬇️ Win = +1 | Loss = -1 | Draw = 0 ⬇️ Picks move with HIGHEST score ⬇️ Result: AI NEVER loses! 🏆 ## 🖼️ Task 3 - Image Captioning ### 📌 Overview An AI that **sees and describes images** by combining Computer Vision and Natural Language Processing using the **BLIP model** by Salesforce. ### ✨ Highlights - 👁️ Computer Vision + NLP combined - 🤖 BLIP pre-trained model by Salesforce - 📝 Generates natural language captions - 📊 Word & character count stats - 🎨 Beautiful animated blue UI ### 🛠️ Tech Stack Language: Python 3.11 Model: BLIP (Salesforce) Framework: Streamlit Libraries: Transformers, PyTorch, Pillow ### 📸 Example Results Image → Sunset landscape Caption → "a river running through a lush green field" ✅ Image → Person in suit Caption → "a man wearing a black suit and tie" ✅ ## 🎬 Task 4 - Recommendation System ### 📌 Overview An **AI movie recommendation system** that suggests similar movies based on content-based filtering using **TF-IDF vectorization** and **cosine similarity**. ### ✨ Highlights - 🎬 48 movies in database - 🤖 TF-IDF + Cosine Similarity algorithm - 📊 Match percentage for each recommendation - 🎭 Genre-based filtering - ⭐ IMDb ratings displayed ### 🛠️ Tech Stack Language: Python 3.11 Framework: Streamlit Algorithm: TF-IDF + Cosine Similarity Libraries: Scikit-learn, Pandas, NumPy ### 🎯 How It Works Select movie you like ⬇️ TF-IDF vectorizes genres ⬇️ Cosine similarity calculated ⬇️ Top 5-10 matches returned ⬇️ Match % displayed! 🎬 ## 👁️ Task 5 - Face Detection ### 📌 Overview An **AI face detection system** that detects and locates faces and eyes in any image using **OpenCV Haar Cascade Classifiers**. ### ✨ Highlights - 👥 Detects multiple faces simultaneously - 👁️ Eye detection within face regions - 🟢 Green boxes around faces - 🔵 Blue boxes around eyes - 📊 Face & eye count display ### 🛠️ Tech Stack Language: Python 3.11 Framework: Streamlit Library: OpenCV Model: Haar Cascade Classifier ### 🔍 Detection Legend 🟢 Green Box → Face Detected 🔵 Blue Box → Eyes Detected ## 🚀 Quick Start # Clone the repository git clone https://github.com/akshatanand-cell/CODSOFT.git # Navigate to any task cd CODSOFT/Task1_Chatbot # Install dependencies pip install streamlit opencv-python-headless Pillow numpy pandas scikit-learn transformers torch # Run the app python -m streamlit run app.py ## 🧠 Skills Gained AI & ML: - Natural Language Processing - Computer Vision - Game Theory & Search Algorithms - Recommendation Systems - Pre-trained Model Integration Programming: - Python 3.11 - Streamlit Web Apps - OpenCV Image Processing - Scikit-learn ML Pipeline Tools: - Git & GitHub - VS Code - OBS Studio ## 📊 Project Stats ## 🤝 Connect With Me