Pattern Recognition with Deep Learning Training Course and Workshop in Bangalore, Mysore, Chennai, Hyderabad, Pune, Mumbai, Delhi, Noida, Gurgaon, Kolkata

The Pattern Recognition with Deep Learning training course focuses on two common pattern recognition problems - image and text recognition. This course starts by introducing the basic concepts and coding on Convolutional Neural Network (CNN) for image recognition. Next, it covers how to diagnose and overcome overfitting issues related to image recognition training on small datasets. Next, it introduces functional API which is used in the subsequent topic of transfer learning to overcome overfitting issues. Finally, we will cover text classification using Recurrent Neural Network (RNN) and word embedding.

By attending Pattern Recognition with Deep Learning workshop, delegates will learn to:

Understand and code CNN models for image recognition
Diagnose overfitting issues in image recognition and propose methods to overcome the issues.
Perform functional API coding based on a selected model.
Implement transfer learning to fine tune the image recognition models.
Understand code RNN models and word embedding for text recognition

Data Scientists
Data Analysts
AI Practitioners

Image Recognition with CNN

Introduction to Convolutional Neural Network (CNN)
Convolution & Pooling
Build a CNN Model for Image Recognition

Overfitting for Small Datasets

Overfitting and Underfitting
Methods to Solve Overfitting
Small Dataset Overfitting Issue
Data Augmentation & Dropout

Functional Keras API

What is Functional API
Create Sequential Model with Functional API
Create Non-Sequential Models with Functional API

Transfer Learning for Small Datasets

Introduction to Transfer Learning
Pre-trained Models
Transfer Learning on Small Dataset

Text Classification with RNN

Introduction to Recurrent Neural Network (RNN)
Types of RNN Architectures
LSTM and GRU
Word Embedding
Build a RNN Model for Text Classification

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