Machine Learning with Scikit Learn Decoded | Python For Machine Learning | Edureka


Python Certification Training for Data Science :
This Edureka session on “Scikit-learn Tutorial” will introduce you to machine learning in Python. It will also take you through regression and clustering techniques along with a demo on SVM classification on the famous iris dataset. This video will help you to learn the below topics:

1. Machine learning Overview
2. Introduction to Scikit-learn
3. Installation of Scikit-learn
4. Regression and Classification
5. Demo

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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 24×7 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 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 Python 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 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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For more information, Please write back to us at or call us at IND: 9606058406 / US: 18338555775 (toll free).




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