- Artificial Intelligence and Machine Learning (AI/ML)
- Supervised Learning
- Machine Learning Algorithms
- Deep Learning
- Artificial Neural Networks
- Applied Machine Learning
- Random Forest Algorithm
- Computer Vision
- Predictive Modeling
- Convolutional Neural Networks
- Natural Language Processing
- Classification Algorithms
Build Decision Trees, SVMs, and Artificial Neural Networks
Completed by Deepak Kumar
April 14, 2024
21 hours (approximately)
Deepak Kumar'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
