Probability and Statistics
@probnstat
Followers
45,341
Following
396
Media
1,080
Statuses
2,211
Probability. Statistics. Machine Learning. Data Science.
Joined September 2022
Don't wanna be here?
Send us removal request.
Explore trending content on Musk Viewer
Kendrick
• 368180 Tweets
Wayne
• 130230 Tweets
Browns
• 105375 Tweets
Watson
• 84265 Tweets
Lions
• 83180 Tweets
Manuel
• 68480 Tweets
Raiders
• 59425 Tweets
重陽の節句
• 59053 Tweets
ON CH3 iQIYI JACK JOKER
• 45470 Tweets
Baker
• 43272 Tweets
#ZEEgotoNYFWwithCOS
• 36381 Tweets
Rams
• 33716 Tweets
もちづきさん
• 19628 Tweets
シーザリオ
• 19540 Tweets
Stafford
• 17870 Tweets
ZEE x COS
• 17574 Tweets
Angélica
• 16282 Tweets
#OnePride
• 16177 Tweets
Yuhui
• 15227 Tweets
Goff
• 12570 Tweets
#GOAT_70Mviews
• 12011 Tweets
JD 3rd ANNIVERSARY
• 11266 Tweets
サッポロポテト
• 11098 Tweets
ふっかさん
• 11022 Tweets
Pinned Tweet
Introduction to Hidden Markov Models (HMMs) by Alperen Degirmenci
Source:
10
363
2K
Computing the Maximum Likelihood Estimator (MLE) for Poisson Distribution.
28
316
2K
On computing the variance of Poisson Distribution.
32
314
2K
On the relationship between Exponential and Geometric distribution.
14
274
2K
Why does Sample Variance have a denominator n-1?
Here is a detailed explanation:
6
285
2K
A clever way to compute expectations of random variables without evaluating integrals.
25
268
2K
Statistics for Mathematicians by Victor M. Panaretos
6
272
2K
On finding the Maximum Likelihood Estimator (MLE) for Exponential Distribution.
13
255
2K
A Modern Introduction to Probability and Statistics by F. M. Dekking, C. Kraaikamp, H. P. Lopuhaä and L. E. Meester
5
232
2K
Machine Learning: The Basics by Alexander Jung
1
233
1K
On computing the mean of Binomial Distributions.
13
182
1K
Stanford CS229: Machine Learning Full Course by Andrew Ng
Source:
5
328
1K
✅ A fantastic problem solving book in probability 👇
18
218
1K
A beautiful reader friendly book on Statistics
15
170
1K
Introduction to Probability Models by Sheldon M. Ross
3
184
1K
📚 Foundations of Statistics for Data Scientists With R and Python 👇
5
184
1K
A Concise Introduction to Mathematical Statistics by Dragi Anevski
1
184
1K
A counterexample to show that convergence in distribution does not imply convergence in probability.
7
131
1K
Computing an integral using the theory of probability distributions.
17
146
1K
📚📖 Finally the book list is out as promised. It is completely free 👇
📊 I am going to update the list continuously from time to time.
✅ Check out the following drive link to keep yourself updated:
27
227
1K
On Back-propagation in Neural Networks
We provide below the following in order to keep the explanation self-contained.
1. Motivation
2. Intuition
3. Mathematical formulation
4. A real-life example
5. Summary
1
238
1K
✅ Full Linear Algebra Course by Gilbert Strang at MIT. 👇
📊 This course is a must if you want to be an expert in machine learning and data science.
🖇️ Playlist link:
3
236
1K
On computing the maximum likelihood estimator of 'p' for a Binomial(n,p) Distribution.
5
134
953
📊 Lecture Notes on Neural Networks 👇
📚 Chapter 8, MIT 6.036, Fall 2019
🖇️ Source (pdf link):
2
226
933
On some convergence results of expectations in probability theory.
3
150
882
Some properties of the Ordinary Least Squares (OLS) Estimate in a regression model with intercepts.
7
134
876
📊 Computing Integrals 👇
🚨 I am planning to start live cohort classes. I am going to teach the basics of probability, statistics, some related mathematics which is necessary to master machine learning and data science. Comment below as well as DM me if you want to enroll 🙂
52
134
855
Perhaps one of the best books on probability theory for self reading.
11
113
852
On Maximum Likelihood Estimation (MLE):
We provide a detailed explanation of MLE in this thread.
Remark: The objective of MLE is to maximize the likelihood function (see image below).
1
138
862
A problem on how to generate Exponential distribution from Uniform distribution.
5
118
819
Statistics for Mathematicians by Victor M. Panaretos
0
135
818
On Brownian Motion and some of its properties
3
130
776
A hardcore mathematical book on statistical learning
Author: Vladimir N. Vapnik
Publisher: Wiley
8
108
757
An interesting problem on the computation of:
1. Conditional Expectation.
2. Conditional Variance.
3
105
758
Proof of existence of the characteristic function of random variables.
5
122
745
Modern Statistics by Ron S. Kenett, Shelemyahu Zacks and Peter Gedeck
5
106
747
An incredible book on Stochastic Processes for beginners
7
97
725
Book: Machine Learning in Finance
Authors: Matthew F. Dixon, Igor Halperin, Paul Bilokon
6
115
709
Calculating variance of linear combinations of random variables
8
130
707
Probability Theory: A Comprehensive Course by Achim Klenke
4
121
713
Mathematical Statistics by Peter J. Bickel and Kjell A. Doksum
1
97
714
On Maximum Likelihood Estimation (MLE)
We provide a self-contained explanation of maximum likelihood estimation below consisting of the following:
1. Motivation
2. Intuition
3. Mathematical formulation
4. A real-life example with computation
5. Summary.
6
161
704
An explanation as to why Mₓ(t):=𝔼(exp(tX)), t∈ℝ is called the Moment Generating Function.
6
102
676
📊 On Markov Chains 👇
🚨 I am planning to start live cohort classes where I am going to teach the basics of probability, statistics, some related mathematics which is necessary to master machine learning and data science. Comment below as well as DM me if you want to enroll 🙂
37
96
666
A clever way to compute probabilities without computing integrals.
8
90
665
📊 Variance of Poisson 👇
🚨 I am planning to start live cohort classes. I am going to teach the basics of probability, statistics, some related mathematics which is necessary to master machine learning and data science. Comment below as well as DM me if you want to enroll 🙂
17
107
669
On the relationship between Exponential and Geometric distribution.
4
99
661
On Logistic Regression Models
Source: The Elements of
Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman
1
132
661
A reader friendly book on the theory of statistics.
6
83
636
A problem with an application of the Central Limit Theorem
1
101
647
Fundamentals of Modern Statistical Methods by Rand R. Wilcox
2
109
635
Algorithms for Data Science by Brian Steele, John Chandler and Swarna Reddy
1
117
642
On computing expectations of functions of Poisson random variables by using infinite series expansions.
6
92
619
Principle of Inclusion-Exclusion in Probability Theory
1
91
625
On Kernel Density Estimation (KDE)
Here we also provide a short R-Code where the frequency distribution of a simulated dataset on daily temperatures is smoothified using the Gaussian Kernel.
1
110
629
914 more to 20K. Well, I have had the fortune of 2,500 in a single day.
Let's see if I can reach 20K today🤞🤞🤞
Thanks a lot for the love you all have showered ❤️
3
44
618
A problem on finding correlation coefficient for Poisson random variables.
2
102
624
A rigorous book on Mathematical Statistics.
Author: Jun Shao.
Publisher: Springer.
3
83
602
A simple example to illustrate a hypothesis testing problem via a one-sample t-test.
7
101
607
On the Gaussian Distribution
Source: Taken from Page 23 of Principal Component Analysis Lecture Notes by Prof. Michale Fee
Link to the Source:
2
127
610
✅ One more problem book in probability and statistics 👇
6
94
601
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference by Dani Gamerman and Hedibert F. Lopes
Link to my upcoming Prob-Stat-ML Course:
DM/Comment if you are interested!
3
118
609
An interesting inequality on the expectation of maximum of two random variables based on their correlation coefficient.
3
87
595
Book: Probability: A Graduate Course
Author: Allan Gut
Publisher: Springer Texts in Statistics
1
81
589
Ten Projects in Applied Statistics by Peter McCullagh
0
106
603
Lecture Notes on Linear Algebra
Author: Richard Earl
Source:
3
116
580
✅ A mathematical perspective on transformers 👇
2
104
569
Probability Theory: A Comprehensive Course by Achim Klenke
1
103
580
