- Artificial Neural Networks
- Decision Tree Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Deep Learning
- Natural Language Processing
- Predictive Modeling
- Convolutional Neural Networks
- Machine Learning Algorithms
- Applied Machine Learning
- Random Forest Algorithm
- Classification Algorithms
- Recurrent Neural Networks (RNNs)
Build Decision Trees, SVMs, and Artificial Neural Networks
Completed by ANKIT SHARMA
November 1, 2023
21 hours (approximately)
ANKIT SHARMA's account is verified. Coursera certifies their successful completion of Build Decision Trees, SVMs, and Artificial Neural Networks
What you will learn
Train and evaluate decision trees and random forests for regression and classification.
Train and evaluate support-vector machines (SVM) for regression and classification.
Train and evaluate multi-layer perceptron (ML) artificial neural networks (ANN) for regression and classification.
Train and evaluate convolutional neural networks (CNN) and recurrent neural networks (RNN) for computer vision and natural language processing tasks.
Skills you will gain
