- Recurrent Neural Networks (RNNs)
- Convolutional Neural Networks
- Computer Vision
- Decision Tree Learning
- Natural Language Processing
- Artificial Neural Networks
- Random Forest Algorithm
- Applied Machine Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Predictive Modeling
- Machine Learning Algorithms
- Supervised Learning
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
