Advanced ML using neural networks.
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Deep learning is a type of machine learning that uses artificial neural networks with multiple layers to learn complex patterns from large amounts of data. It enables computers to perform tasks such as recognizing images, understanding speech, processing language, and generating text or videos.
Deep learning is inspired in part by the structure of the human brain, although artificial neural networks work differently from biological brains.
How Does Deep Learning Work?
Data collection: The system receives data such as images, text, audio, or numerical information.
Input layer: Data enters the neural network.
Hidden layers: Multiple layers process the data and learn increasingly complex patterns.
Training: The network adjusts its internal parameters to reduce errors or improve its objective.
Output layer: The system produces a result, such as a prediction, classification, or generated response.
Examples of Deep Learning
Image recognition: Identifies objects, faces, and products in images.
Speech recognition: Converts spoken language into text.
Natural language processing: Helps AI systems understand and generate human language.
Generative AI: Powers many systems that generate text, images, audio, and video.
Recommendation systems: Helps identify patterns in user behavior to recommend relevant products.
Fraud detection: Identifies suspicious patterns in transactions or other data.
Example in Ecommerce
A Shopify jewellery store can use a deep-learning-powered visual search system. A customer uploads a picture of a necklace, and the system analyzes visual features to find similar products in the store’s catalog.
The system’s accuracy depends on the quality of product images, the model, and the available data.
Deep Learning vs. Machine Learning
Machine learning: The broader field of algorithms that learn patterns from data.
Deep learning: A subset of machine learning that uses neural networks with multiple layers to learn complex representations.
Deep learning can perform very well on complex tasks but often requires more data and computing resources than simpler machine-learning methods.
In short: Deep learning is a branch of machine learning that uses multilayer neural networks to learn complex patterns. It is a key technology behind many modern AI applications, including image recognition, language models, and generative AI.