Objetivo

Ao participar do Curso Keras Advanced & Sequential Data Modeling, os participantes aprenderão:

• Ajuste de hiperparâmetros com Keras e Auto-Keras
• Retornos de chamada
• API funcional para construir modelos complexos
• Backend Keras para invocar operações Tensorflow
• Auto-Keras
• Recapitulação de RNN e LSTM
• Convolução 1D
• Modelo de sequência de sequência 2
• Mecanismo de Atenção

Publico Alvo

• Data Scientists
• Data Analysts
• Engineers

Pre-Requisitos

• Python básico
• Keras Básico
• Aprendizado de máquina

Materiais

Conteúdo Programatico

Recap on Keras Basic

1. Sequential Model
2. Feedforward Neural Network (NN)
3. Convolutional Neural Network (CNN)
4. Recurrent Neural Network (RNN)

Functional API

1. What is Functional API
2. Code Sequential Models with Functional API
3. Fine Tune Transfer Learning with Functional API
4. Implement GAN with Functional API
5. Create Multi Input and Output Model

Callbacks

1. Keras Callbacks
2. ModelCheckPoint Callback
3. Tensorboard Callback

Data Generator

1. Image Class Generator
2. Fit Generator
3. Flow from Directory Generator
4. Custom Data Generator

Keras Backend

1. What is Keras Backend
2. Keras Backend Commands
3. Create Custom Loss Function

Word Embedding

1. One Hot Encoding of Words
2. Word Embedding
3. Pre-Trained Word Embedding

RNN and LSTM

1. Recurrent Neural Network (RNN)
2. Long Short Term Memory (LSTM) and GRU
3. Stacked RNN
4. Bidirectional RNN
5. Case Studies on Time Series Prediction with LSTM

1D Convolution

1. 1D Convolution on Sequential Data
2. Combining 1D Convolution and RNN

Sequence To Sequence Model

1. What is Seq2Seq Model
2. Attention Mechanism