Machine learning and neural networks are pillars on which you can build intelligent
applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing
you to Python and discussing AI search algorithms. You will cover in-depth mathematical
topics, such as regression and classification, illustrated by Python examples.
As you make your way through the course, you will progress to advanced AI techniques
and concepts, and work on real-life datasets to form decision trees and clusters. You will be
introduced to neural networks, a powerful tool based on Moore’s law.
Tujuan
- Understand the importance, principles, and fields of AI
- Implement basic Artificial Intelligence concepts with Python
- Apply regression and classification concepts to real-world problems
- Perform predictive analysis using decision trees and random forests
- Carry out clustering using the k-means and mean shift algorithms
- Understand the fundamentals of deep learning via practical examples
Materi Pokok
- Lesson 1: Principles of Artificial Intelligence
- Fields and Applications of Artificial Intelligence
- AI Tools and Learning Models
- The Role of Python in Artificial Intelligence
- Python for Game AI
- Lesson 2: AI with Search Techniques and Games
- Heuristics
- Pathfinding with the A* Algorithm
- Game AI with the Minmax Algorithm and Alpha-Beta Pruning
- Lesson 3: Regression
- Linear Regression with One Variable
- Linear Regression with Multiple Variables
- Polynomial and Support Vector Regression
- Lesson 4: Classification
- The Fundamentals of Classification
- Classification with Support Vector Machines
- Lesson 5: Using Trees for Predictive Analysis
- Introduction to Decision Trees
- Random Forest Classifier
- Lesson 6: Clustering
- Introduction to Clustering
- The k-means Algorithm
- Mean Shift Algorithm
- Lesson 7: Deep Learning with Neural Networks
- TensorFlow for Python
- Introduction to Neural Networks
- Deep Learning
