For all those that are feeling a bit lost, here is a simplified guide to the key concepts
Artificial intelligence, Deep learning, Large Language Models,
💥 Artificial Intelligence (AI) - In simple terms
Is a branch of computer science that aims to create machines capable of imitating human intelligence.
🖳 Machine Learning (ML)
Systems that can learn and adapt using algorithms and statistical models to analyze and draw inferences from patterns found in data. The real magic is its ability to do so without explicit instructions, much like a self-taught prodigy.
🕸 Neural Networks (NN)
Mirroring the human brain, these algorithms form a 'digital brain' constructed from layers of nodes that recognize patterns by interpreting data through a kind of machine perception, labeling, or clustering raw input.
👮 Supervised learning
Supervised learning refers to ML models that are trained on labelled data. It is like learning with a teacher. AI is provided with a dataset that includes ‘right answers‘. AI ‘learn’ from both previous input data and the previous results (which represent the labels), and is later used to predict an outcome based on new, unlabeled input data.
👶 Unsupervised learning.
In contrast to supervised learning, unsupervised learning refers to ML models that are trained only on unlabeled inputs. It is like learning without a teacher. The algorithm is not given 'right answers'/ labels ahead of time. Its task is to find patterns or structures within the input data on its own.
🕵 Deep Learning (DL)
Deep learning is a ML method based on neural networks composed of multiple layers. It is like a detective who is great at solving complex mysteries using many clues. It works by processing data through multiple layers (the clues), with each layer taking the output from the previous one, refining it, and passing it to the next. The "deep" in deep learning refers to the many layers it uses – the more layers, the deeper the learning.
🗪 Natural Language Processing (NLP)
NLP refers to the branch of AI concerned with processing text and spoken words and understanding their meaning. It allows machines to understand and respond to voice or text inputs in natural language, or even generate human-like text.
👁 Computer Vision
This involves teaching computers to "see" and understand the content of digital images such as photographs and videos.
And there you have it - a basic understanding of Artificial Intelligence in simple terms - it is your foundation to start journey of the AI world!
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