Improving Data Quality In Data Analytics & Machine Learning

[dkmdkm]

Free Download Improving Data Quality In Data Analytics & Machine Learning
Last updated 11/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.99 GB | Duration: 5h 23m
Learn why, when, and how to maximize the quality of your data to optimize data-based decisions

What you'll learn
Strategies for increasing data quality
Ways to assess data quality
Interpreting data visualizations
How to spot problems in data
Requirements
Interest in working with data
Interest in knowing more about data quality
Some Python skills are useful for the optional coding videos
Description
All of our decisions are based on data. Our sense organs gather data, our memories are data, and our gut-instincts are data. If you want to make good decisions, you need to have high-quality data.This course is about data quality: What it means, why it's important, and how you can increase the quality of your data. In this course, you will learn:High-level strategies for ensuring high data quality, including terminology, data documentation and management, and the different research phases in which you can check and increase data quality.Qualitative and quantitative methods for evaluating data quality, including visual inspection, error rates, and outliers. Python code is provided to see how to implement these visualizations and scoring methods using pandas, numpy, seaborn, and matplotlib.Specific data methods and algorithms for cleaning data and rejecting bad or unusual data. As above, Python code is provided to see how to implement these procedures using pandas, numpy, seaborn, and matplotlib.This course is for Data practitioners who want to understand both the high-level strategies and the low-level procedures for evaluating and improving data quality.Managers, clients, and collaborators who want to understand the importance of data quality, even if they are not working directly with data.
Data science practitioners,Data scientist students,Managers or colleagues who work with data practitioners
Homepage

Bitte Anmelden oder Registrieren um Links zu sehen.

Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

No Password - Links are Interchangeable

 

[0dayddl]

Improving data quality in data analytics & machine learning
Last updated 11/2025
Duration: 5h 23m | .MP4 1920x1080 30fps(r) | AAC, 44100Hz, 2ch | 1.99 GB
Genre: eLearning | Language: English​

Learn why, when, and how to maximize the quality of your data to optimize data-based decisions

What you'll learn
- Strategies for data quality
- Ways to assess data quality
- Interpreting data visualizations
- How to spot problems in data

Requirements
- Interest in working with data
- Interest in knowing more about data quality
- Some Python skills are useful for the optional coding videos

Description
All of our decisions are based on data. Our sense organs gather data, our memories are data, and our gut-instincts are data. If you want to make good decisions, you need to have high-quality data.

This course is about data quality: What it means, why it's important, and how you can increase the quality of your data.

In this course, you will learn:

High-level strategies for ensuring high data quality, including terminology, data documentation and management, and the different research phases in which you can check and increase data quality.

Qualitative and quantitative methods for evaluating data quality, including visual inspection, error rates, and outliers. Python code is provided to see how to implement these visualizations and scoring methods using pandas, numpy, seaborn, and matplotlib.

Specific data methods and algorithms for cleaning data and rejecting bad or unusual data. As above, Python code is provided to see how to implement these procedures using pandas, numpy, seaborn, and matplotlib.

This course is for

Data practitioners who want to understand both the high-level strategies and the low-level procedures for evaluating and improving data quality.

Managers, clients, and collaborators who want to understand the importance of data quality, even if they are not working directly with data.

Who this course is for:
- Data science practitioners
- Data scientist students
- Managers or colleagues who work with data practitioners

Bitte Anmelden oder Registrieren um Links zu sehen.

DDownload

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

RapidGator

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

NitroFlare

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!