Free Machine Learning Resources from Accelebrate
Are there different types of Machine Learning? Yes, they are supervised, unsupervised, and reinforcement learning.
- The most common type of ML involves supervised learning, in which an algorithm is given a set of labeled data and learns to predict the label for new data.
- Unsupervised learning is used when the algorithm is not given any labeled data and learns to find patterns in the data.
- Reinforcement learning is used when the algorithm is rewarded for actions that lead to a desired outcome. The algorithm then learns to take actions that maximize the reward.
AI, ML, Neural Networks, and Deep Learning: What's the Difference?
- AI is an umbrella term, meaning any system exhibiting intelligent behavior.
- ML is a type of AI that allows systems to learn without being explicitly programmed. ML algorithms learn from data by identifying patterns and making predictions.
- Neural Networks have interconnected nodes (artificial neurons) that process information. Neural networks are algorithms used in machine learning.
- Deep learning uses complex neural networks many layers deep to process and handle large amounts of complex data, such as images, text, or speech.
View our breakdown of Artificial Intelligence infographic for more information and examples.
Machine Learning Webinar
To learn more about Machine Learning with Python, watch our 1-hr pre-recorded Webinar:
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