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Embark on a comprehensive 9-hour Hindi tutorial series designed to introduce beginners to TensorFlow, a powerful library for deep learning in Python. Start with the basics of installing TensorFlow 2.0 and setting up your development environment. Explore fundamental concepts of neural networks, activation functions, and cost functions. Progress through hands-on lessons covering TensorFlow syntax, graphs, variables, and placeholders. Build your first perceptron and neural network, then dive into practical applications with regression and classification examples. Tackle real-world projects like house price prediction and salary classification. Advance to more complex topics, working with the MNIST dataset using both basic approaches and Convolutional Neural Networks (CNNs). Conclude with additional insights into manual TensorFlow backend operations and setting up OpenAI Gym for reinforcement learning experiments.
