Deep Learning is a subset of Machine Learning that uses artificial neural networks with many layers to process data, identify patterns, and make predictions. It powers systems that perform complex tasks such as image recognition, speech processing, and natural language understanding.
How Deep Learning Works
At the core of deep learning are neural networks built to mimic how the human brain processes information. A deep learning model consists of an input layer, multiple hidden layers, and an output layer. Each layer transforms the data before passing it to the next.
The model learns by adjusting weights during training. It processes large volumes of data and tunes itself using a method called backpropagation. Over time, it improves its accuracy without needing human intervention.
Deep learning needs large datasets and powerful hardware. It works well when traditional algorithms fall short, especially in tasks with high-dimensional input like images or audio.
Where It Is Used
Deep learning is used in many real-world applications. Self-driving cars use it to detect objects. Smartphones use it for voice assistants and facial recognition. Healthcare systems use it to analyse medical scans. Financial firms use it to detect fraud based on transaction patterns.
In India, sectors like IT, healthcare, and telecom are adopting deep learning for automation, quality control, and predictive analysis. It helps reduce manual effort and improves precision in decision-making.
What You Should Know
Deep learning is not the best fit for every problem. It works well when you have enough data and compute power. It can also be hard to interpret, which makes explainability a concern in regulated industries.
