Скачать или смотреть Knowledge Representation in AI | Semantic Networks | Artificial Intelligence Tutorial | Edureka

** AI & ML Masters Program - https://www.edureka.co/masters-progra... **
This Edureka video on "Knowledge Representation in AI" will explain what is knowledge representation and how reasoning works in AI. It will explain the different techniques to represent knowledge.
(Blog: https://www.edureka.co/blog/knowledge... )

-----------------------------------------------------------

Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

Instagram:   / edureka_learning  
Slideshare: https://www.slideshare.net/EdurekaIN/
Facebook:   / edurekain  
Twitter:   / edurekain  
LinkedIn:   / edureka  

#edureka #edurekaAI #artificialIntelligence #KnowledgeRepresentation #artificialintelligencetutorial
-----------------------------------------------------------
About the course:

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

-----------------------------------------------------------

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyze Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyze data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

-----------------------------------------------------------

Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

If you are looking for live online training, write back to us at [email protected] or call us at (Toll-Free) US: + 18338555775 or India: +91 9606058406 for more information.