Build Decision Trees, SVMs, and Artificial Neural Networks

There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and support-vector machines (SVMs) are two examples of algorithms that can both solve regression and classification problems, but which have different applications. Likewise, a more advanced approach to machine learning, called deep learning, uses artificial neural networks (ANNs) to solve these types of probl

• Train and evaluate decision trees and random forests
• Train and evaluate support-vector machines for regression and classification
• Train and evaluate multi-layer perceptron neural networks
• Train and evaluate CNNs and RNNs for vision and NLP tasks

• Basic programming knowledge
• Understanding of fundamental machine learning concepts
• Analytical math knowledge including linear algebra and statistics