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Artificial intelligence course in Chandigarh

Our brains contain billions of interconnected neurons.Neurons receive signals, process them, and pass them on.<br>Learning occurs by strengthening or weakening connections between neurons.<br>

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Artificial intelligence course in Chandigarh

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Presentation Transcript

  1. Neural Networks in Artificial Intelligence

  2. Inspiration Our brains contain billions of interconnected neurons.Neurons receive signals, process them, and pass them on. Learning occurs by strengthening or weakening connections between neurons. Artificial neural networks attempt to mimic this process. Artificial neurons receive inputs, process them, and generate outputs. The strength of connections between artificial neurons is adjusted during training.

  3. How Neural Networks Work Inputs: Data enters the network through the input layer. Hidden Layers: Layers of interconnected 'neurons' perform calculations. Output Layer: Generates the final result (classification, prediction, etc.). Weights: Connections between neurons have weights that get adjusted during learning. Activation Functions: Determine how a neuron 'fires' based on its input.

  4. Introduction • AI is the simulation of human intelligence by machines. • AI revolutionizes technology across industries. • Overview of AI, history, types, applications, and future. • Examples: Speech recognition, problem-solving. • From symbolic AI to deep learning. • Invitation to explore AI basics.

  5. What is AI?

  6. History of AI • Origin: Dartmouth Conference in 1956. • Development: Symbolic AI, expert systems. • AI Winters: Periods of reduced interest and funding. • Resurgence: Neural networks, deep learning in 2010s. • Milestones: Turing Test, Deep Blue vs. Kasparov. • Current era: Rapid advancement and integration into daily life.

  7. Types of AI

  8. Applications of AI • Healthcare: Diagnosis, personalized treatment. • Finance: Fraud detection, algorithmic trading. • Automotive: Autonomous vehicles, predictive maintenance. • Retail: Customer service chatbots, personalized recommendations. • Education: Adaptive learning, grading automation. • Entertainment: Content recommendation, gaming assistants.

  9. Machine Learning

  10. Deep Learning • Subfield of machine learning inspired by the human brain. • Neural networks with multiple layers for hierarchical data representation. • Applications: Image classification, speech recognition. • Advancements in hardware (GPUs) and algorithms drive success. • Challenges: Interpretability, computational resources. • Pioneering architectures: Convolutional Neural Networks (CNNs), Transformers.

  11. Conclusion

  12. Artificial intelligence course in Chandigarh For Query Contact : 998874-1983

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