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Python for Deep Learning

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At a Glance

The Python for Deep Learning course is designed to provide participants with a comprehensive understanding of deep learning concepts and techniques using Python. Participants will learn how to build and train deep neural networks using popular deep learning frameworks such as TensorFlow and Keras.

Objectives

By the end of the course, participants will be equipped to:

Understand the fundamentals of deep learning and its applications
Learn how to implement deep neural networks using Python and TensorFlow
Gain proficiency in building and training convolutional neural networks (CNNs)
Master recurrent neural networks (RNNs)
Explore advanced topics in deep learning, including transfer learning, generative adversarial networks (GANs), and reinforcement learning
Apply deep learning techniques to real-world datasets and projects

Prerequisite

Basic knowledge of Python programming and familiarity with machine learning concepts is required. Prior experience with neural networks and deep learning is helpful but not required.

Curriculum

8 Sections
20h Duration

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Introduction to Deep Learning with Python

Building and Training Deep Neural Networks

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Advanced Deep Learning Techniques

Reinforcement Learning with Python

Model Deployment and Productionizing

Implementation of Deep Learning Techniques in Industry-relevant Problems

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