Machine Learning Courses at Dicoding: https://www.dicoding.com/academies/184
What materials will be studied?
- Data Introduction : Introduction to data and how to prepare it for processing with machine learning.
- Unsupervised & Supervised Data: Understanding 2 types of machine learning, namely unsupervised and supervised, with examples of linear regression models and decision trees.
- Kernel and Clustering: Get to know the Support Vector machine, a very popular machine learning model. Here also learn about clustering with k-means.
- Machine Learning Basics: Understand how to use grid search to find the best parameters for a model, and how to test the quality of a machine learning model.
- Neural Networks: Get to know the basics of neural networks. We will explain about multi-layer perceptron and convolutional neural networks in image classification.
- Tensorflow : Learn about the tensorflow library, a powerful library used to develop machine learning projects.
- Create Models with IBM Watson Studio
- The project has objective to recognize the shape of the hand that forms scissors, rock, or paper from image.