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Mathematics for ML | Machine Learning Training | Edureka | ML Rewind - 5

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Machine Learning
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Published on 05/26/24 / In How-to & Learning

🔥Edureka*** Machine Learning Certification Training - https://www.edureka.co/machine....-learning-certificat ***

00:00 Introduction
01:10 Agenda
01:28 Why Mathematics in Machine learning
03:38 Linear Algebra
05:05 Linear ALgebra - Scalars
06:20 Linear Algebra - Vectors
11:27 Linear Algebra - Matrices
20:24 Linear Algebra - Vector as Matrix
26:11 Linear Algebra - Eigen Vectors
27:41 Linear Algebra - Applications
30:18 Multivariate Calculus

Data Science Training: https://www.edureka.co/data-sc....ience-r-programming-

This Edureka video on "Clustering Algorithms" will help you understand the various aspects of clustering using K Means in Python.

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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.

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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. Analyse 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. Analyse 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

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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.

For online Data Science training write to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free).

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