🤖Machine learning is a subdomain of computer science that focuses on algorithms that help computers learn from data.
🔍Supervised learning uses labeled inputs and outputs to train models and make predictions.
🧠Unsupervised learning learns patterns from unlabeled data.
🏆Reinforcement learning uses rewards and penalties to train models in an interactive environment.
📚Data science is a field that finds patterns and insights from data, often using machine learning techniques.
What is the difference between machine learning and artificial intelligence?
—Machine learning is a subset of artificial intelligence that focuses on algorithms that learn from data.
What is supervised learning?
—Supervised learning is a type of machine learning that uses labeled data to train models and make predictions.
What is unsupervised learning?
—Unsupervised learning is a type of machine learning that discovers patterns from unlabeled data.
What is reinforcement learning?
—Reinforcement learning is a type of machine learning that uses rewards and penalties to train models in an interactive environment.
What is data science?
—Data science is a field that focuses on finding patterns and insights from data using various techniques, including machine learning.
00:00Introduction to machine learning and its different types.
07:40Overview of TensorFlow and its use in machine learning.
10:09Explanation of supervised learning and its importance in machine learning.
11:29Understanding the difference between machine learning, artificial intelligence, and data science.
13:04Explanation of unsupervised learning and how it discovers patterns from unlabeled data.
13:59Overview of reinforcement learning and its use of rewards and penalties to train models.
17:43Introduction to data science and its focus on finding patterns and insights from data.
