Data Science Algorithms Full Course | Data Science Tutorial For Beginners | Simplilearn

Data Science Algorithms Full Course | Data Science Tutorial For Beginners | Simplilearn

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This video on Data Science algorithms will help you learn some of the essential data science algorithms used by data scientists to work on complex tasks. You will implement these algorithms using Python and R. These algorithms use supervised and unsupervised learning methods to train models.

Below are the topics covered in this Data Science Algorithms Full Course video:
00:00:00 Logistic regression
00:19:37 Decision tree
01:28:14 Clustering Algorithm
02:09:54 SVM Algorithm
02:28:03 K-Means Clustering
02:54:30 Naive Bayes Classifiers
04:25:35 Time series analysis

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Below Data Science algorithms are explained in this tutorial:
logistic Regression
Types of Regression
Decision Tree
What is Random forest
Clustering Algorithm
Divisive Clustering
Support Vector Machine in R
K-Nearest Neighbors Algorithm
K-Means Clustering
Time-series Analysis

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#DataScienceAlgorithms #DataScienceAlgorithmsWithExamples #DataScienceForBeginners #DataScience #DataScienceTutorial #DataScienceTutorialForBeginners #Simplilearn

This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.

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Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.

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Install the required Python environment and other auxiliary tools and libraries
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Data Science Algorithms Full Course | Data Science Tutorial For Beginners | Simplilearn

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