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"Join the best Deep Learning course in Jalandhar, Punjab, at TechCadd. Master neural networks and AI techniques with practical, hands-on training!
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BEST DEEP LEARNING COURSE JALANDHAR https://techcadd.com/ +91-9888122255
WHAT IS DEEP LEARNING? • Subset of Machine Learning • Uses multi-layered neural networks • Learns from large amounts of data • Great for unstructured data: images, audio, text
HOW DEEP LEARNING WORKS • Neural networks simulate human brain • Composed of input layer, hidden layers, output layer • Learns by adjusting weights using backpropagation
KEY TERMINOLOGIES Epoch Underfitting Batch size Overfitting Learning rate Loss function
Basic structure: neurons, layers, weights, biases • Feedforward + backpropagation explained simply • Activation functions: ReLU, Sigmoid, Tanh NEURAL NETWORKS OVERVIEW
TYPES OF DEEP NEURAL NETWORKS • Convolutional Neural Networks (CNNs) – Image recognition • Recurrent Neural Networks (RNNs) – Sequence prediction (e.g., time series, NLP) • Autoencoders – Dimensionality reduction • GANs (Generative Adversarial Networks) – Content generation
RECURRENT NEURAL NETWORKS (RNNS) • Used in text, speech, time-series • Maintains state/memory across sequences • Variants: LSTM, GRU
REAL-WORLD APPLICATIONS • Computer Vision: Facial recognition, medical imaging • Natural Language Processing: Chatbots, language translation • Autonomous Vehicles: Object detection & driving decisions • Voice Assistants: Speech-to-text (e.g., Siri, Alexa)
Requires large labeled datasets CHALLENGES IN DEEP LEARNING High computational power Interpretability of results Risk of overfitting
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