Deep & Sequential Deep Learning

Many factors influenced the rise of AI and the launch of the fourth technological revolution. However, one primary invention that accelerated the process was the ability to transform images into information. This breakthrough paved the way for transforming videos, texts, and audio into information, resulting in advancements such as driverless cars, boots, and automation that almost match human abilities. This workshop focuses on the algorithms behind this technological breakthrough, making AI a reality and allowing you to apply deep learning and Sequential Deep Learning algorithms to solve new, challenging problems.

Workshop Overview

Learning Outcomes

• Learn the mathematics behind Deep Learning.

• Explore the logic of optimization with Gradient Descent.

• Dissect components of neural networks.

• Adjust hyperparameters of algorithms to optimize cost functions.

• Explore the architecture of main deep learning networks.

• Improve the accuracy of Classification and Estimation.

• Establish knowledge in:

  • Image classification

  • Face recognition

  • Object detection

• Apply Sentiment Analysis.

Detailed Course Schedule

• Day 1:

  • Algebra and Calculus

• Day 2:

  • Gradient Descent

  • Perceptron Algorithm

• Day 3:

  • Feedforward Neural Networks

• Day 4:

  • Convolutional Neural Networks

• Day 5:

  • Recurrent Neural Networks

  • LSTM and GRU

• Comprehensive colored PPT booklet.

• Neurons, Hidden layers, Synapsis, ...

• Weights, Scores, ...

• Activation functions: Sigmoid, TanH, ...

• SoftMax rule

• Feed Forward of information

• Backpropagation

• Convolution windows, MaxReLu, ...

• TensorFlow coding applications

What will it be about?