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PostNetwork Academy
Добавлен 5 сен 2017
I am Bindeshwar Singh Kushwaha, founder of PostNetwork Academy (www.postnetwork.co).This channel walks you through, computer programming, mathematics, statistics,
A. I., Machine Learning, Deep Learning, Data Science, Internet of Things and Robotics from basics to advance level. Moreover, you will also get to know about research and
development in the respective fields.
Will you support me??
Subscribe the channel.
A. I., Machine Learning, Deep Learning, Data Science, Internet of Things and Robotics from basics to advance level. Moreover, you will also get to know about research and
development in the respective fields.
Will you support me??
Subscribe the channel.
Classical or Mathematical Probability Video #124 Data Sc. and A.I.
RUclips Video Description
Master Classical or Mathematical Probability
Welcome to PostNetwork Academy! In this video, we dive into the fundamentals of **Classical or Mathematical Probability**, an essential concept in mathematics and statistics. Whether you're a student or an enthusiast, this video will guide you step by step.
📚 **What You'll Learn:**
- Definition of Classical Probability and its core formula.
- Key properties and assumptions of probability.
- Examples: Tossing a coin and rolling a die.
- Limitations: Biased coins and infinite sample spaces.
- A summary to consolidate your learning.
✍️ **Key Formula:**
\[
P(A) = \frac{\text{Number of Favorable Outcomes (m)}}{\text{Total Numb...
Master Classical or Mathematical Probability
Welcome to PostNetwork Academy! In this video, we dive into the fundamentals of **Classical or Mathematical Probability**, an essential concept in mathematics and statistics. Whether you're a student or an enthusiast, this video will guide you step by step.
📚 **What You'll Learn:**
- Definition of Classical Probability and its core formula.
- Key properties and assumptions of probability.
- Examples: Tossing a coin and rolling a die.
- Limitations: Biased coins and infinite sample spaces.
- A summary to consolidate your learning.
✍️ **Key Formula:**
\[
P(A) = \frac{\text{Number of Favorable Outcomes (m)}}{\text{Total Numb...
Просмотров: 1
Видео
Exhaustive, Favourable, Mutually Exclusive, and Equally Likely Cases Video #123 Data Sc. and A.I.
Просмотров 24 часа назад
Master Probability Concepts: Exhaustive, Favourable, Mutually Exclusive, and Equally Likely Cases Welcome to the Data Science and A.I. Lecture Series by PostNetwork Academy, hosted by Bindeshwar Singh Kushwaha. 🚀 In this video, we break down key probability concepts essential for understanding random experiments and statistical analysis: - Exhaustive Cases: Learn about the total possible outcom...
Sample Space, Point and Events Video #122 Data Sc. and A.I.
9 часов назад
Understanding Probability: Sample Space, Sample Points, and Events Welcome to PostNetwork Academy's Data Science and AI Lecture Series. In this video, Bindeshwar Singh Kushwaha explains the fundamental concepts of probability, including sample space, sample points, and events. What you'll learn: - The meaning of sample space and how to determine it - Examples of sample points in random experime...
Deterministic to Random: The Role of Probability in AI and Data Sc. Video #121 Data Sc. and A.I.
Просмотров 19 часов назад
Deterministic to Random: The Role of Probability in AI and Data Science Welcome to the Data Science and AI Lecture Series presented by Bindeshwar Singh Kushwaha at PostNetwork Academy. In this insightful session, we explore the fascinating transition from deterministic systems to random experiments and how probability underpins the foundation of AI and data science. 📚 What You’ll Learn: ✅ What ...
Spearman's Coefficient of Correlation Video #120| Data Science & A.I.
14 часов назад
Are you struggling to understand Spearman's Rank Correlation Coefficient? 🤔 This video provides a clear and concise explanation of this essential statistical concept! 📊 ✨ What You'll Learn in This Video: ✅ The need for Spearman's Rank Correlation Coefficient ✅ How it differs from Pearson's Correlation ✅ Step-by-step calculation with an example (Lipstick Rankings!) ✅ The formula: 𝑟 𝑠 = 1 − 6 ∑ 𝑑...
Derivation of Correlation Coefficient Property Video #119| Data Science & A.I.
14 часов назад
Welcome to PostNetwork Academy! In this video, Bindeshwar Singh Kushwaha walks you through the complete derivation of the correlation coefficient 𝑟 ( 𝑋 , 𝑌 ) r(X,Y), a key formula in statistics and data science. 🔍 What You'll Learn: The mathematical definition of the correlation coefficient. Key concepts: variance, covariance, and their relationships. Step-by-step breakdown of the derivation pr...
Karl Pearson's Correlation −1≤r(X,Y)≤1 Video #118| Data Science & A.I.
Просмотров 416 часов назад
In this video, Bindeshwar Singh Kushwaha, from PostNetwork Academy, walks you through the proof that the Karl Pearson's correlation coefficient, \(r(X, Y)\), always lies between -1 and 1. This result is crucial in data science and statistics, as it helps to quantify the strength and direction of the linear relationship between two variables. We break down the proof into easy-to-understand steps...
Karl Pearson's Correlation Coefficient Numerical Example Video #117| Data Science & A.I.
Просмотров 616 часов назад
Understanding Karl Pearson's Correlation Coefficient Welcome to PostNetwork Academy! In this video, we dive into Karl Pearson's Coefficient of Correlation , a fundamental concept in statistics and data science. 🌐 📌 What You’ll Learn : - What is Karl Pearson's Correlation Coefficient? - How to calculate it step-by-step with an example. - Understanding the relationship between two variables. 📝 Ex...
Independence of Origin and Scale in Correlation Coefficient Video #116| Data Science & A.I.
Просмотров 119 часов назад
Discover the mathematical elegance behind Karl Pearson's Correlation Coefficient in this insightful lecture by Bindeshwar Singh Kushwaha, presented by PostNetwork Academy. Explore how the correlation coefficient remains invariant under linear transformations, ensuring its robustness as a measure of linear association. This video is part of our Data Science and A.I. Lecture Series, designed to e...
The Definition and Calculation of The Correlation Coefficient Video #115 | Data Science and A.I.
Просмотров 921 час назад
The Definition and Calculation of the Correlation Coefficient Welcome to PostNetwork Academy's Data Science and A.I. Lecture Series! In this video, Bindeshwar Singh Kushwaha explains the concept of the correlation coefficient , its formula, and how to calculate it step-by-step. This lecture is perfect for students, professionals, and enthusiasts aiming to strengthen their understanding of data ...
Why is Covariance Bounded? The Power of Cauchy-Schwarz Inequality Video #114 | Data Science and A.I.
Просмотров 2День назад
Why is Covariance Bounded? | The Power of Cauchy-Schwarz Inequality In this video, we explore the relationship between covariance and standard deviation, revealing why the absolute value of covariance is bounded. Using the Cauchy-Schwarz Inequality, we derive the mathematical foundation behind this bound and illustrate it with step-by-step examples. 🔍 Topics Covered: 1️⃣ Covariance and Standard...
Understanding Correlation: Simplified Explanation! Video #113 | Data Science and A.I.
Просмотров 1День назад
Welcome to PostNetwork Academy! In this video, we break down the concept of correlation in the simplest way possible. Learn how to measure the strength and direction of relationships between variables, understand its formula, and explore real-life examples. Perfect for data science enthusiasts, students, and professionals! 🎯 What You'll Learn: ✔️ What is Correlation? ✔️ The Difference Between P...
Covariance: A Numerical Example :! Video #111 | Data Science and A.I.
Просмотров 2День назад
In this video, we explore the concept of covariance with a practical numerical example. Learn how to calculate covariance between two variables, understand its interpretation, and distinguish it from correlation. This tutorial is part of the Data Science and AI Lecture Series presented by Bindeshwar Singh Kushwaha from PostNetwork Academy. #DataScience #AI #Covariance #Statistics #PostNetworkAc...
Angle Finder using Arduino Uno and Gyro Sensor
Просмотров 165День назад
Angle Finder using Arduino Uno and Gyro Sensor
Covariance: Discover How Data Variables Connect :! Video #111 | Data Science and A.I.
Просмотров 714 дней назад
Covariance: Discover How Data Variables Connect :! Video #111 | Data Science and A.I.
Covariance Explained: Change of Origin vs. Scale Made Simple! Video #110 | Data Science and A.I.
Просмотров 514 дней назад
Covariance Explained: Change of Origin vs. Scale Made Simple! Video #110 | Data Science and A.I.
Covariance Simplified: Learn It Once, Understand It Forever! Video #|109 Data Science and A.I.
Просмотров 114 дней назад
Covariance Simplified: Learn It Once, Understand It Forever! Video #|109 Data Science and A.I.
IoT Based Pulse Monitoring : Cardio Mitra
Просмотров 1714 дней назад
IoT Based Pulse Monitoring : Cardio Mitra
Bivariate Distribution Made Simple: From Definition to Covariance Calculation Video #108 | DS & AI
Просмотров 414 дней назад
Bivariate Distribution Made Simple: From Definition to Covariance Calculation Video #108 | DS & AI
Moments and Pearson's Coefficient Simplified Video #107 | Data Science & A.I. Lecture Series
Просмотров 621 день назад
Moments and Pearson's Coefficient Simplified Video #107 | Data Science & A.I. Lecture Series
Very helpful video
Very good video sir🎉
Nice video
Tailedness refers to tails, while peakedness/flatness refers to center. Further, kurtosis does not tell you anything about the peak. There are low perfectly flat-topped distributions with very high kurtosis, and there are infinitely peaked distributions with very low kurtosis.
Nice video
Nice
Very nice video
Very knowledge full video sir
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❤
Very good video sir
Very helpful video ❤
🎉
Nice video
Tumhara ci galat h
Very good video
Veri good video
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Thanks
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Great work❤
Sir I am Your student
Nice and helpful😊
Thanks 😊
Great👍
👍 spb
❤❤
❤❤
Fantastic video😊
Good🎉🎉🎉🎉🎉🎉
Good🎉🎉
Sir what you have said I understand all the things from aditya
Very good sir form Akshay ❤❤
Nice video
Thanks
Good 💯
Thanks 🔥
Umm ok good pushkar Oh sorry professor pushkar Pathak.
Great bro..
Thank you Sir
😆 'Promosm'
Wah Puskar! Good job beta❤❤
-cosx
Correct
Nice
😅
🎉
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Excellent harshit...keep going👍
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Nice explain ❤
5:59 a=7 b=5 c=(a+b)**2 print(c) We can also use this line of code since if we factories a²+2ab+b² that equals to (a+b)² .
love it
nice
very meaning video