diff --git a/Domains/AI-ML/MiniProjects/Emotion_classifier/README.md b/Domains/AI-ML/MiniProjects/Emotion_classifier/README.md
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+**Contributor:** Ansh-1019
+
+# 🎭 Real-Time Emotion Detection using DeepFace and OpenCV
+
+This project detects human emotions in real-time using a webcam feed.  
+It utilizes the **DeepFace** library for emotion analysis and **OpenCV** for face detection and visualization.
+
+---
+
+## 🚀 Features
+
+- Detects emotions such as **happy**, **sad**, **angry**, **surprise**, **neutral**, and more.  
+- Works in **real-time** using your webcam.  
+- Displays bounding boxes and emotion labels on detected faces.  
+- Gracefully handles frames without detectable faces.
+
+---
+
+## 🧠 Technologies Used
+
+- **Python 3.8+**
+- **OpenCV** – for capturing webcam feed and drawing on frames.
+- **DeepFace** – for facial emotion analysis.
+- **Haar Cascade Classifier** – for basic face detection.
+
+---
+
+## 📦 Installation
+
+### 1️⃣ Clone or Download the Repository
+```bash
+git clone https://github.com/yourusername/emotion-detection.git
+cd emotion-detection
+```
+
+---
+
+## ▶️ How to Run
+
+1. Save the provided code as **`emotion.py`** in your project folder.  
+2. Open **Command Prompt** or **Terminal** in that folder.  
+3. Run the script:
+
+   ```bash
+   python emotion.py
+    ```
+4. Your webcam will open automatically.  
+5. A bounding box with your detected emotion will appear on screen.  
+6. Press **`q`** to quit the program.
diff --git a/Domains/AI-ML/MiniProjects/Emotion_classifier/emotion.py b/Domains/AI-ML/MiniProjects/Emotion_classifier/emotion.py
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+import cv2
+from deepface import DeepFace
+
+
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    try:
+        
+        result = DeepFace.analyze(frame, actions=['emotion'], enforce_detection=False)
+        
+        
+        if isinstance(result, list):
+            emotion = result[0]['dominant_emotion']
+        else:
+            emotion = result['dominant_emotion']
+
+        
+        face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+        faces = face_cascade.detectMultiScale(frame, 1.3, 5)
+
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+            cv2.putText(frame, emotion, (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
+
+    except Exception as e:
+        
+        print("No face detected or error:", e)
+        
+        cv2.putText(frame, "No face detected", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
+
+    
+    cv2.imshow('Emotion Detection', frame)
+
+    
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+
+cap.release()
+cv2.destroyAllWindows()
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diff --git a/Domains/AI-ML/MiniProjects/Voice_Assistant/README.md b/Domains/AI-ML/MiniProjects/Voice_Assistant/README.md
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+**Contributor:** Ansh-1019
+
+# 🧠 Voice Assistant – Friday
+
+A beginner-friendly Python voice assistant that listens, understands, and responds to your voice commands. This project was built to explore speech recognition, text-to-speech, and smart command execution in Python.
+
+## 🚀 Features
+
+- 🎤 **Voice Input** — Recognizes your voice using the microphone  
+- 🕓 **Tells the Time and Date** — Fetches current time and date on command  
+- 🎵 **Plays Songs** — Plays songs on YouTube using `pywhatkit`  
+- 😂 **Tells Jokes** — Lightens the mood with a random joke  
+- 📖 **Wikipedia Summaries** — Provides brief summaries from Wikipedia  
+- 🌐 **Google Search** — Searches the web for any topic  
+- 🧠 **Wake Word Detection** — Activates when you say **"Friday"**
+
+## 🛠️ Tech Stack
+
+- Python 3.13  
+- `speech_recognition` – Speech-to-text  
+- `pyttsx3` – Text-to-speech  
+- `pywhatkit` – YouTube/Google automation  
+- `wikipedia` – Search summaries  
+- `pyjokes` – Random jokes for fun  
+
+## 🗂️ Project Structure
+* `friday.py`: The main entry point for running the voice assistant.
+* `stt.py`: Contains modules and functions related to Speech-to-Text conversion.
+* `tts.py`: Contains modules and functions related to Text-to-Speech conversion.
+* `combine.py`: (Optional) This file is for experimental code merging features.
+* `README.md`: This file, providing an overview and instructions for the project.
+---
+
+## 🚀 Getting Started
+
+To run the assistant:
+
+```bash
+python friday.py
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diff --git a/Domains/AI-ML/MiniProjects/Voice_Assistant/friday.py b/Domains/AI-ML/MiniProjects/Voice_Assistant/friday.py
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+++ b/Domains/AI-ML/MiniProjects/Voice_Assistant/friday.py
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+import speech_recognition as sr
+import pyttsx3
+import datetime
+import pywhatkit
+import pyjokes
+import wikipedia
+
+def taking_command():
+    r = sr.Recognizer()
+
+    with sr.Microphone() as source:
+        print("Calibrating background noise...")
+        r.adjust_for_ambient_noise(source,duration=0.3)
+        print("Listening...")
+        audio = r.listen(source)
+    try:
+        text= r.recognize_google(audio)
+        print(text)
+        return(text)
+    except sr.RequestError:
+        print("check your internet")
+        responding("check your internet")
+    except sr.UnknownValueError:
+        print("cannot understand")
+        responding("cannot understand")
+
+def responding(text):
+    engine = pyttsx3.init()
+    voices = engine.getProperty('voices')
+    engine.setProperty('voice', voices[2].id)
+    engine.say(text)
+    engine.runAndWait()
+
+def function():
+    audio=taking_command()
+
+    if audio is None:
+        return
+
+    audio=audio.lower()
+
+    if 'time' in audio:
+       time= datetime.datetime.now().strftime('%I:%M %p')
+       print("current time is "+time)
+       responding("current time is "+time)
+
+    elif 'play' in audio:
+        song= audio.replace('play','').strip()
+        responding("playing"+song)
+        pywhatkit.playonyt(song)
+    
+    elif 'joke' in audio:
+        joke=pyjokes.get_joke()
+        print(joke)
+        responding(joke)
+
+    elif 'tell me' in audio:
+        inf= audio.replace('tell me','')
+        info= wikipedia.summary(inf ,2)
+        print(info)
+        responding(info)
+
+    elif 'date' in audio:
+        date= datetime.datetime.today().strftime('%d %B %Y')
+        print("today's date is "+date)
+        responding("today's date is "+date)
+        
+    elif 'google' in audio:
+        data= audio.replace('google','').strip()
+        responding("googling"+data)
+        pywhatkit.search(data)
+
+def wake_word():
+    while True:
+        text = taking_command()
+        if text and 'friday' in text.lower():
+            responding("yes captain, what can i do for you")
+            return
+
+if __name__=="__main__":
+    responding("friday activated")
+    while True:
+        wake_word()
+        function()
+        
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