Deep Learning with TensorFlow is a comprehensive course designed to help learners understand and implement deep learning models using TensorFlow and Keras. This course covers the fundamentals of neural networks, deep learning architectures, and real-world applications such as image recognition and natural language processing.
You will learn how to build, train, and optimize deep neural networks using industry-standard tools. Through hands-on projects and real-world datasets, this course equips you with the skills required to work on advanced AI systems and prepares you for a career in deep learning and artificial intelligence.
Topics of Course
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Introduction to Deep Learning
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Understanding Neural Networks
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Introduction to TensorFlow
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Building Your First Neural Network
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Understanding Neurons and Network Architecture
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Activation Functions
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Forward and Backpropagation
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Loss Functions and Optimization Techniques
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Introduction to TensorFlow Keras APIs
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Building Sequential Models
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Building Functional Models
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Training and Evaluating Models
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Introduction to CNNs
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Convolution and Pooling Layers
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CNN Architectures
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Applications of CNNs
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Introduction to RNNs
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LSTM and GRU Networks
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Introduction to NLP
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Sequence Modeling Applications
