Developing AI and ML Solutions with Java E-learning
Bestel deze geweldige E-learning Training Developing AI and ML Solutions with Java online cursus, 1 jaar 24/ 7 toegang tot rijke interactieve video’s, spraak, praktijkopdrachten, voortgangsbewaking door rapportages en testen per onderwerp om de kennis direct te toetsen. Na de cursus ontvangt u een certificaat van deelname.
Kursinhalt
Developing AI and ML Solutions with Java: AI Fundamentals
Course: 1 Hour, 4 Minutes
Development Environment for Artificial Intelligence
Machine Learning with Java
Artificial Intelligence Implementation Scenarios
Deeplearning4J Introduction
Configure Neural Network Using DL4J
Domain Specific Implementation of AI
Predictive Modeling
Exercise: Working with ML Libraries
Developing AI and ML Solutions with Java: Machine Learning Implementation
Course: 1 Hour, 27 Minutes
Machine Learning Algorithm Types
Supervised and Unsupervised Learning
K-Means Cluster
KNN Algorithms
Decision Tree and Random Forest
Linear Regression Analysis
Gradient Boosting Algorithms
Logistics Regression
Probabilistic Classifier
Naïve Bayes Classifier
Exercise: Implementing Machine Learning Algorithms
Course Test
Developing AI and ML Solutions with Java: Neural Network and Neuroph Framework
Course: 1 Hour, 49 Minutes
Neural Network and its Essential Components
Implement a Simple Neural Network
Neural Network Types
Implementing Hopfield Neural Networks
Implementing Back Propagation Neural Networks
Role of Activation Function
Loss Functions and their Benefits
Implementing Activation Functions and Loss Functions
Hyperparameter
Neuroph Java Neural Framework Capabilities
Hyperparameter Implementation using DL4J
Deep Learning
Comparing Deep Learning and Graph Models
Combining Deep Learning and Graph Model1
Deep Learning and Graph Model Use Cases
Exercise: Working with Neuroph and Neural Networks
Developing AI and ML Solutions with Java: Neural Network and NLP Implementation
Course: 57 Minutes
Multilayer Networks and Computation Graphs
Implementing Multilayer Networks
NLP Introduction
Components of NLP
Language and Sentence
Tokenizer and Name Finder
Detecting Parts of Speech
Classifying Text and Documents
Using Parser to Extract Relationships
Speech Implementation
Exercise: Working with NLP Components
Developing AI and ML Solutions with Java: Expert Systems and Reinforcement Learning
Course: 48 Minutes
Expert Systems Tools
Working with Jess
Defining Rules
Supervised Learning and Notations
Datasets and Training Models
Outlier Types
Feature Search and Feature Evaluation Techniques
Principal Component Analysis Data Transformation
Clustering Concept
Hierarchical Clustering
Graph Modeling
Exercise: Working with Datasets and Clustering
Lassen Sie uns helfen!
| Studiengebühr: | 5 Stunden Dauer plus Übungen (variabel) |
| Sprache: | Englisch |
| Online-Zugang: | 1 Jahr |
| Teilnahmebescheinigung: | Ja, nach 70% der erfolgreichen Einsätze |
| Fortschrittsüberwachung: | Ja |
| Geeignet für Handys: | Ja |
| Preisgekröntes E-Learning: | Ja |
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