Free Machine Learning Resources from Accelebrate
Are there different types of Machine Learning? Yes, they are supervised, unsupervised, and reinforcement learning.
- Supervised learning is the most common type of ML, and the algorithm is given a set of labeled data. The algorithm then 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, and Deep Learning: What's the Difference?
- AI is an umbrella term, meaning any system exhibiting intelligent behavior. ML and deep learning are specific techniques that can be used to achieve AI goals.
- 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.
- Deep learning is part of ML and uses artificial neural networks (ANNs) to learn from data. Neural networks mimic the human brain and can perform complex tasks by analyzing large amounts of data.
To learn more about Machine Learning with Python, watch our 1-hr pre-recorded Webinar:
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