Exploring Machine Learning E-Learning Ausbildung

Bestellen Sie diesen einzigartigen E-Learning-Kurs Online Exploring Machine Learning, 1 Jahr rund um die Uhr Zugriff auf umfangreiche interaktive Videos, Sprache, Fortschrittsüberwachung durch Berichte und Kapiteltests, um das Wissen direkt zu test.

Kursinhalt

Introduction to Machine Learning and Supervised Learning

Course: 55 Minutes

• Course Introduction
• What is Machine Learning?
• Supervised Learning
• How to Build Models
• Overfitting
• Precision and Recall

Supervised Learning Models

Course: 41 Minutes

• Course Introduction
• Classification vs. Regression
• Regression Trees
• CART Decision Tree Learning
• Random Forests
• Random Forests with Python
• Logistic Regression Model
• Logistic Regression in Python
• Support Vector Machines (SVM)
• Kernel Methods for SVMs
• Support Vector Machines in Python
• Naïve Bayes Classifiers
• Naïve Bayes Classifiers in Python

Unsupervised Learning

Course: 33 Minutes

• Course Introduction
• What is Unsupervised Learning?

Neural Networks

Course: 40 Minutes

• Course Introduction
• Defining Neural Networks
• Neural Network Structures
• Cost Functions for Neural Networks
• Activation Functions
• Training Neural Networks
• Training Neural Networks With Backpropagation
• Batch Learning

Convolutional and Recurrent Neural Networks

Course: 41 Minutes

• Course Introduction
• Introducing Convolutional Neural Networks (CNNs)
• CNN Architecture
• Convolution Layers
• Pooling Layer
• CNN Training Considerations
• Regularization
• Convolutional Neural Network Implementation
• Regularization Methods for CNNs

Applying Machine Learning

Course: 39 Minutes

• Course Introduction
• Bias and Variance
• Cross-validation
• Cross-validation in Python
• Metrics for Binary Classification Models
• Metrics for Non-binary Classification Models
• Classification Metrics in Python
• Metrics for Regression Models
• Regression Metrics in Python