• 0945 09 09 08
  • support@hspace.vn

Machine learning for Computer Vision

Course time: Duration: 45
Duration 45 Credits
Categories Skills, Computer Vision

This course is designed to provide an overview of basic machine learning applied to the computer vision field. Also introduce an overview process when working with machine learning projects. Provide knowledge and skills to use important algorithms such as Linear Regression, Logistic Regression, KNN, K-mean, Decision Tree, Random Forest, SVM, AdaBoost, PCA, SVD. The algorithms introduced come with practical applications related to the computer vision field.

Part 1: Introduction

  • Introduce machine learning
  • Classify algorithms
  • Introducing python programming language, how to install libraries and related tools

Part 2: Basic algorithms

  • Linear regression
  • Logistic regression
  • K-Nearest Neighbor (KNN)
  • Clustering with K-mean
  • Naïve Bayes classifier

Part 3: Working process of a machine learning project

  • Data collection
  • Money handling data
  • Feature extract
  • Algorithms selection, model training
  • Review model
  • Adjust the parameters of the model
  • Application deployment

Part 4: Advanced algorithms

  • Decision Tree
  • Random Forest
  • Support Vector Machine
  • Boosting, AdaBoost
  • Principal Component Analysis (PCA)
  • Singlar Value Decomposition (SVD)

Part 5: Application

  • Problem of object detection
  • Problem identifying objects

hSpace Team

hSpace Team

hSpace Team

Mechinelearning