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Machine Learning in Python

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Updated On 02 Feb, 19

Overview

Machine Learning Tutorial in Python helps you gain expertise in various types of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Through this playlist you will be learning the important Machine Learning concepts and its implementation in python programming language.

Includes

Lecture 41: Data Science vs Machine Learning – What’s The Difference? | Data Science Course | Edureka

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Lecture Details

** Python Data Science Training: https://www.edureka.co/data-science-python-certification-course **
In this video on Data Science vs Machine Learning, we’ll be discussing the importance of Data Science and Machine Learning and we’ll compare them based on a few key parameters. The following topics are covered in this session:

(00:47)What Is Data Science?
(02:32)What Is Machine Learning?
(04:06)Fields Of Data Science
(05:32)Use Case

Python Training Playlist: https://goo.gl/Na1p9G
Python Blog Series: https://bit.ly/2RVzcVE

PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai

Post Graduate Certification in Data Science with IIT Guwahati - https://www.edureka.co/post-graduate/data-science-program
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)

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#edureka #datascience #machinelearning #datasciencevsmachinelearning
How it Works?

1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work

2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.

3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

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About the Course

Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Data Science Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.

During our Python Certification Training, our instructors will help you to:

1. Master the basic and advanced concepts of Python

2. Gain insight into the Roles played by a Machine Learning Engineer

3. Automate data analysis using python

4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application

5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn

6. Explain Time Series and it’s related concepts

7. Perform Text Mining and Sentimental analysis

8. Gain expertise to handle business in the future, living the present

9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands-on Project Experience

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Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built-in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other
scientific computations.

Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and Dot NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

For online Data Science training, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

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Comments
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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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