Fast track to Machine Learning, Data Science and Steganography course

Fast track to ML, Data Science and Steganography

Standard measures / metrics of ML, Data Science & Steganography

Rating: 3.9 out of 5

3.9 (27 ratings)

7,954 students

Created by Dipnarayan Das

Last updated 6/2020

English : English [Auto]

What you'll learn

• General / Statistical Measures
• Data Science measures / metrics
• Machine Learning measures / metrics
• Steganography measures / metrics

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Requirements

• For Machine Learning metrices basics of ML should be cleared
• For Steganography, basic Cryptography and Image Processing should be known

Description

Guide:

Aanchal Singhal

This is a brand new Machine Learning, Data Science, and Steganography based course updated with the latest trends and skills!

This is the first course in Udemy which will provide you detailed information about Steganography.

The topics covered in this course are:

- General / Statistical Measures

- Data Science Measures

- Machine Learning Measures / Performance metrics

- Steganography Measures / Metrics

Like every presentation need the final touch, this course will cover your gaps in Data Science, Machine Learning, and also in the newly trending topic Steganography. By the end of this course, you can be a Machine Learning, Data Scientist, Steganography expert, and can be get hired at large companies. This course will straight forward deliver rich information to users. Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.

See you inside the course!

Who this course is for:

• Data Science Enthusiast
• Machine Learning Enthusiast
• Image Processing Enthusiast
• Cryptography Enthusiast
• Statistics enthusiast

Course content

6 sections • 45 lectures • 38m total length

Preview

General / Statistical Measure's Index

Confusion Matrix

Sensitivity

Precision

Specificity

PPV & NPV

Fall out

FDR

Miss Rate

Accuracy

F-score

Centrality measure

Mean

Median

Mode

Spread / Dispersion Measure

Range

Variance

Standard Deviation

Data Science Measure's Index

Grouping

Cross tab

Pivot table

Imputation

Data filling Algorithm

Outlier Detection

Machine Learning Measure's Index

MCC

Box plot

Radar plot

ROC-AUC

Steganography Measure's Index

Histogram

MSE

PSNR

SSIM

Chi-square

RS Analysis

StegExpose

Embedded Capacity

FOBP

Bit Rate

Conclusion

Instructor : Dipnarayan Das

Founder at Perity. Full Stack Developer. Researcher

4.0 Instructor Rating

42 Reviews

10,298 Students

2 Courses