Developing Advanced Machine Learning Applications with Python and Tensorflow
About This Course
Embark on a transformative journey with our WSQ-endorsed Pattern Recognition with Deep Learning course. You will delve into core concepts such as neural networks, feature extraction, and machine learning algorithms. Through hands-on projects and case studies, you'll gain practical experience in recognizing patterns and applying deep learning techniques to various types of data.
By the end of this course, you'll have a robust skill set in pattern recognition using deep learning methods. Whether you're a data scientist looking to specialize, or a professional in fields requiring complex data analysis, this course will empower you with the expertise to make insightful, data-driven decisions.
What You'll Learn
- 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
Course Outline:
Topic 1 Image Recognition with CNN
Introduction to Convolutional Neural Network (CNN)
Convolution & Pooling
Build a CNN Model for Image Recognition
Topic 2 Overfitting for Small Datasets
Overfitting and Underfitting
Methods to Solve Overfitting
Small Dataset Overfitting Issue
Data Augmentation & Dropout
Topic 3 Functional Keras API
What is Functional API
Create Sequential Model with Functional API
Create Non-Sequential Models with Functional API
Topic 4 Transfer Learning for Small Datasets
Introduction to Transfer Learning
Pre-trained Models
Transfer Learning on Small Dataset
Topic 5 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
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
• Minimum 18 years old