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Machine Learning : Data Preprocessing in Hindi

Free Hindi Data Science Course ( Machine Learning ): Data Preprocessing: Correlation, Data Molding, Null Values

Beginner 0(0 Ratings) 0 Students enrolled
Created by Rishi Bansal Last updated Fri, 02-Oct-2020 English
What will i learn?
  • What is Data Preprocessing?
  • What are various types of Data Preprocessing and why we need it.

Curriculum for this course
11 Lessons 00:42:43 Hours
Machine Learning : Data Preprocessing
11 Lessons 00:42:43 Hours
  • What is Data Preprocessing? 00:07:00
  • Checking for Null Values: Concept + Python Code 00:07:08
  • Correlated Feature Check: Concept + Python Code 00:07:08
  • Data Molding(Encoding): Concept + Python Code 00:00:00
  • Data Splitting : Python Code 00:05:30
  • Data Splitting : Python Code 00:10:00
  • Impute Missing Values: Concept + Python Code 00:00:00
  • Scaling in Machine Learning 00:05:57
  • Scaling: Python Code 00:00:00
  • Label Encoder: Concept + Code 00:00:00
  • One-Hot Encoder: Concept + Python Code 00:00:00
Requirements
  • Knowledge of Python is required for Coding section
  • After completing this course, you can connect to me on my blog for any question.
  • No prerequisite. Anyone can do this course.
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Description

This course is designed to understand the basic concept of data preprocessing. Anyone can opt for this course. No prior understanding of machine learning is required. The data pre-processing concept and its implementation in Python are covered in detail.

यह कोर्स Data Preprocessing की मूल अवधारणा को समझने के लिए बनाया गया है। कोई भी इस कोर्स का विकल्प चुन सकता है। Machine Learning की कोई पूर्व समझ आवश्यक नहीं है। इस कोर्स में data pre-processing अवधारणा और इसके कार्यान्वयन को विस्तार से कवर किया गया है।


Data quality is critical to a successful machine learning model. Data preprocessing is a prerequisite for machine learning. We cannot feed into machine learning algorithms as raw data. It is important to clean the data, analyze it, and transform it to understand machine learning algorithms.

एक सफल मशीन लर्निंग मॉडल के लिए डेटा की गुणवत्ता महत्वपूर्ण है। मशीन प्रीप्रोसेसिंग मशीन सीखने के लिए एक शर्त है। हम मशीन लर्निंग algorithms को raw data के रूप में  feed  नहीं कर सकते हैं। डेटा को clean करना, उसका विश्लेषण करना और उसे मशीन लर्निंग algorithms को समझने के लिए बदलना महत्वपूर्ण है।


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About the instructor
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A total of 13 years of experience. I started my career as a programmer.  Apart from programming, I have worked on Cloud & Virtualization technology, DevOps and Machine Learning. Also, I have very good knowledge of software design methodologies, information systems architecture, object oriented design, and software design patterns. Teaching is my passion.  I hope you will enjoy my course.

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Free
Includes:
  • 00:42:43 Hours On demand videos
  • 11 Lessons
  • Full lifetime access
  • Access on mobile and tv