Differences between AI/ML/DL

Description

  • Artificial Intelligence (AI) is the broad field of creating intelligent systems capable of simulating human intelligence such as learning, reasoning, problem-solving, and perception.
  • Machine Learning (ML)is a subset of AI that focuses on systems learning from data to improve their performance without being explicitly programmed.
  • Deep Learning (DL) is a specialized subset of ML using artificial neural networks with multiple layers to model complex patterns and representations in large datasets.

Examples (Code)

Below is a simple example of AI using python to create a rule-based system:

# AI Example - Simple rule-based system
def chatbot(input_text):
    if "hello" in input_text.lower():
        return "Hi! How can I help you?"
    return "I didn't understand that."

# ML Example - Predicting house prices
from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X_train, y_train)
predictions = model.predict(X_test)

# DL Example - Image classification using deep neural networks
from keras.models import Sequential
from keras.layers import Dense
model = Sequential([
    Dense(128, activation='relu', input_shape=(784,)),
    Dense(10, activation='softmax')
])
model.compile(optimizer='adam', loss='categorical_crossentropy')
model.fit(X_train, y_train, epochs=10)

Real-World Applications

Artificial Intelligence

Used in self-driving cars, smart assistants, and facial recognition.

Machine Learning

Used in spam filtering, recommendation systems, and credit scoring.

Deep Learning

Used in voice assistants, image classification, and language translation.

Where AI Is Applied

Domain AI ML DL
Healthcare Robotic surgery, virtual nurses Disease prediction models Medical image analysis
Finance Fraud detection, robo-advisors Credit scoring, risk modeling Document analysis using NLP
Retail Chatbots, personalized offers Customer segmentation Vision-based shelf monitoring
Transportation Autonomous navigation systems Route optimization Pedestrian detection in vehicles

Resources

Additional resources

Interview Questions with Answers

What is the difference between AI and ML?

AI is the broader concept of machines being able to carry out tasks in a smart way, while ML is a subset of AI that enables systems to learn from data.

How does Deep Learning differ from Machine Learning?

Deep Learning uses neural networks with many layers to learn complex patterns. ML typically involves simpler models like decision trees or linear regression.

Is every ML system an AI system?

Yes, all ML systems are a part of AI, but not all AI systems use ML. Some are rule-based or use search algorithms.

Can Deep Learning work without Machine Learning?

No. Deep Learning is a subset of Machine Learning. It requires the ML foundation to function.

Give an example where AI is used but not ML.

A rule-based chatbot that follows if-else statements is AI but doesn't use ML.