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A Hindi-language playlist covering the math behind machine learning: probability and statistics, linear algebra and calculus, with chapter timestamps showing a long run through each area.
The first large block covers probability, conditional probability, Bayes' theorem, combinatorics, random variables, the normal distribution and the central limit theorem. Hypothesis testing follows, with z, t, chi-square and ANOVA tests and a QQ plot demonstration.
Beginners who prefer Hindi explanations and want the statistics that machine learning relies on, taught in a clear order. Interview-question segments appear within the probability section.
Probability and statistics notes, link-
https://ownstreet.in/datadissection/shop
Telegram group- https://t.me/data_dissection
Full Machine Learning course in hindi- https://youtube.com/playlist?list=PLlpUUtQ9RrF4o3UTYbc4cP3NCEyE5BwX5&si=RVj6gVjE2J0XwPw8
Full Neural networks course- https://youtube.com/playlist?list=PLlpUUtQ9RrF47CpLH6PSFL2oeP3izPMhE&si=xJ5E79pugCDkYxR7
Math for ai
math for machine learning math for data science probability for machine learning probability for data science machine learning machine learning roadmap machine learning full course machine learning projects machine learning engineer roadmap machine learning tutorial machine learning playlist machine learning course machine learning interview questions machine learning machine learning full course in hindi machine learning in tamil machine learning in telugu machine learning with python Welcome to this comprehensive Machine Learning Course in Hindi . In this playlist, you'll master the essential machine learning algorithms with hands-on coding tutorials, real-world examples, and step-by-step explanations.
00:00:00 - Introduction to course
00:00:56 - Introduction to Probability
00:02:56 - Probability definition
00:14:03 - Set theory
00:22:04 - Fair events
00:25:23 - Conditional Probability
00:36:30 - Types of events
00:43:16 - Bayes Theorem
01:00:34 - Combinatorics
01:31:49 - Random variables
01:36:45 - Mean, Median and Mode
01:45:06 - Standard Deviation
01:53:30 - Expectation
02:05:48 - Covariance
02:18:06 - Correlation
02:28:27 - Binomial Distribution
02:34:23 - Probability Distribution Functions
02:55:20 - Normal Distribution and Z-score
03:08:07 - Microsoft Data Science interview quesn
03:18:56 - PhonePe interview quesn
03:25:39 - Statistics, Population and samples
03:37:53 - Central Limit Theorem
03:50:16 - QQ plot
03:56:46 - QQ plot code
04:01:42 - Hypothesis Testing(Null hypothesis)
04:18:16 - 2 tailed test
04:33:53 - Z Test
04:45:30 - T Test
04:54:14 - 2 sample test
05:09:33 - KS Test
05:21:49 - Chi square test
05:35:03 - ANOVA
05:45:22 - F Test
05:52:18 - Introduction to Linear Algebra
05:53:51 - Straight lines
06:00:51 - Co-ordinate geometry
06:17:07 - Vectors
06:29:24 - Matrix
06:41:19 - Determinants
06:48:44 - Eigen value & Eigen vectors
06:53:46 - Introduction to calculus
06:56:34 - Functions
07:08:41 - More on functions
07:37:12 - Limits and deriving dy/dx
07:49:16 - Rules of dy/dx
07:56:16 - Application of dy/dx
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