Neural Networks With Deep Learning Training Course in Chicago

Neural Networks with Deep Learning Training Course Outline

Module 1: Introduction to Neural Networks

• Introduction to Neural Networks
• Supervised Learning with Neural Networks

Module 2: Neural Networks Fundamentals

• Binary Classification
• Logistic Regression
• Gradient Descent and Derivatives
• Computational Graph
• Vectorisation
• Introduction to Python
• Jupyter/IPython Notebooks

Module 3: Shallow Neural Networks

• Representation of a Neural Networks
• Computing the Output of a Neural Network
• Vectorised Implementation
  • Feed Forward
  • Back Propagation
• Hidden Layer
• Activation Functions
• Gradient Descent for Neural Networks

Module 4: Deep Neural Networks

• Deep L-Layer Neural Network
• Forward Propagation
• Computational Graphs
• Backward Propagation
• Neural Networks Training
• Deep Representations
• Building Blocks
• Difference Between Parameters and Hyperparameters

Who Should Attend this Neural Networks with Deep Learning Training Course?

The Neural Networks with Deep Learning Course is designed for individuals working in Data Science, Artificial Intelligence, and related fields who wish to deepen their understanding and practical skills in Deep Learning. The following are some professionals for whom this course can be beneficial:

• Data Scientists
• AI Engineers
• Software Developers
• Machine Learning Engineers
• Researchers
• Analysts
• IT Professionals

Prerequisites of the Neural Networks with Deep Learning Training Course

There are no formal prerequisites for this Neural Networks with Deep Learning Course. However, a basic understanding of programming and familiarity with Machine Learning concepts would be beneficial.

Neural Networks with Deep Learning Training Course Overview

Neural Networks with Deep Learning Training Course provides an introduction to Neural Network concepts and the techniques used to build Deep Learning models. It covers supervised learning, logistic regression, gradient descent, vectorisation, Deep Neural Networks, and computational graphs.

Delegates will gain knowledge of Neural Network principles while developing skills in understanding Neural Network architectures, forward and backward propagation, activation functions, feedforward networks, and model optimisation techniques.

This 1-Day course by The Knowledge Academy enables delegates to interpret Neural Network models, apply foundational Deep Learning techniques, and support the development of AI-driven solutions across a range of applications.

Neural Networks with Deep Learning Training Course Objectives

• To understand the foundational principles of neural networks
• To explore various deep learning architectures, including CNNs and RNNs
• To apply Deep Learning algorithms in image and speech recognition tasks
• To analyse and interpret profound learning model results effectively
• To optimise and fine-tune neural networks for improved performance
• To comprehend ethical considerations in deploying deep learning solutions

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise deep learning models using TensorFlow, making them invaluable assets in their professional fields.

What’s Included in this Neural Networks with Deep Learning Training Course?

• World-Class Training Sessions from Experienced Instructors
• Neural Networks with Deep Learning Certificate
• Digital Delegate Pack