Frequently Asked Questions (FAQs) about Machine Learning

Intermediate

❓ Frequently Asked Questions (FAQs) About Machine Learning

Q1: What is the difference between AI, machine learning, and deep learning?

🧠 AI is a broad concept of creating intelligent machines
🔁 ML is a subset focused on algorithms that learn from data
🧬 Deep Learning is a subset of ML that uses neural networks with many layers

Q2: Do I need programming skills to learn ML?

💻 Yes, proficiency in programming languages like Python or R is essential to implement and experiment with algorithms.

Q3: How much data is needed for ML?

📊 It depends on the problem complexity.
📈 Generally, more data leads to better models, but quality often outweighs quantity.

Q4: Can ML models be biased?

⚠️ Yes, models can reflect biases present in training data, making fairness and bias mitigation critical components of ML workflows.

Q5: How do I choose the right algorithm?

🎯 Start with:

  • Problem type
  • Data characteristics
  • Resource constraints

🧪 Experimentation and validation are key to selecting optimal models.