Building Your First Machine Learning Model with Python and Tensorflow
About This Course
Embark on your journey into the realm of artificial intelligence with our WSQ-endorsed Basic Deep Learning with Tensorflow Keras course. This course provides an in-depth understanding of fundamental deep learning concepts, focusing on neural network architectures and how to implement them using Tensorflow Keras. With hands-on exercises and real-world examples, you'll learn the basics of designing, training, and tuning neural networks for various tasks, from natural language processing to image recognition.
By the end of this course, you’ll possess a foundational understanding of deep learning techniques. You'll be capable of using Tensorflow Keras to build and train basic neural network models. Whether you're looking to transition into the burgeoning field of AI, or you're a professional seeking to add deep learning to your skill set, this course is your stepping stone towards expertise in artificial intelligence.
What You'll Learn
setup Tensorflow and Keras Deep Learning frameworks
understand and code Neural Network models for Regression
understand and code Neural Network models for Classification
understand and code Convolutional Neural Network models for Image Classification
understand and use pre-trained models for transfer learning
Course Outline:
Topic 1 Introduction to Deep Learning
- Machine Learning vs Deep Learning
- Deep Learning Methodology
- Overview of Tensorflow and Keras
- Install and Run Keras
Topic 2 Introduction to Neural Network
- What is Neural Network (NN)?
- Loss Function and Optimizer
- Build a Neural Network Model for Regression
Topic 3 Classification with Neural Network
- One Hot Encoding and SoftMax
- Cross Entropy Loss Function
- Build a Neural Network Model for Classification
Topic 4 Image Classification with Convolutional Neural Network (CNN)
- Introduction to Convolutional Neural Network?
- ImageDataGenerator
- Image Classification Model with CNN
- Data Augmentation and Dropout
Topic 5 Transfer Learning with Pre-trained Models
- Introduction to Transfer Learning
- Applications of Pre-Trained Models
- Fine Tuning Pre-Trained Models
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