- Natural Language Processing
- Machine Learning Algorithms
- Applied Machine Learning
- Computer Vision
- Deep Learning
- Predictive Modeling
- Classification Algorithms
- Recurrent Neural Networks (RNNs)
- Artificial Intelligence and Machine Learning (AI/ML)
- Random Forest Algorithm
- Supervised Learning
- Artificial Neural Networks
Build Decision Trees, SVMs, and Artificial Neural Networks
Completed by Yuvraj Chopra
November 1, 2023
21 hours (approximately)
Yuvraj Chopra '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
