Machine Learning (ML) is a subset of artificial intelligence (AI) that enables machines to learn from data without being explicitly programmed. Netguru, a leading tech company, has outlined 18 crucial concepts in the realm of AI, ML, and Large Language Models (LLMs). Let’s delve into some of these fundamental concepts:
1. Supervised Learning
In supervised learning, algorithms learn from labeled training data to make predictions or decisions. It involves mapping an input to an output based on example input-output pairs.
2. Unsupervised Learning
Unsupervised learning deals with uncovering hidden patterns or intrinsic structures in data without explicit labels. Clustering and dimensionality reduction are common unsupervised learning techniques.
3. Neural Networks
Neural networks are a series of algorithms designed to recognize patterns. They mimic the human brain’s structure and are used in various applications like image and speech recognition.
4. Deep Learning
Deep learning is a subset of ML that uses neural networks with multiple layers to model and process complex data. It has revolutionized fields like computer vision and natural language processing.
5. Reinforcement Learning
Reinforcement learning involves an agent learning to make decisions by interacting with an environment to achieve a goal. It is commonly used in robotics and gaming.
6. Natural Language Processing (NLP)
NLP focuses on the interaction between computers and humans using natural language. It enables machines to understand, interpret, and generate human language.
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7. Transfer Learning
Transfer learning involves leveraging knowledge from one task to improve learning in another related task. It helps in training models with limited data.
These are just a few of the essential concepts in the vast field of machine learning. To explore the complete list of 18 crucial concepts by Netguru, visit their official website.
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