28:57
The Coin Flip Game that Stumped Twitter: Alice HH vs Bob HT
88K views • 1 month ago
35:56
Business Math - Intro to the course [ LECTURE RECORDING ] MATH1030 - See playlist in description
768 views • 2 months ago
30:15
The Math of "The Trillion Dollar Equation"
78K views • 4 months ago
1:12:26
[Lecture] Monte Carlo evaluation and control: A Gridworld Example | Intro to Markov Chains and RL
572 views • 4 months ago
1:05:42
[Lecture] Is it safe to differentiate under the integral? Lebesgue Dominated Convergence theorem
403 views • 4 months ago
1:02:19
[ Lecture ] Intro to Monte Carlo methods in Reinforcement Learning | Intro to Markov Chains and RL
144 views • 4 months ago
1:14:15
[ Lecture ] Almost Everywhere vs L1 convergence and an absolute summability theorem | Intro Analysis
110 views • 4 months ago
1:06:16
[ Lecture ] L1 is complete and the monotone convergence theorem for integrals | Intro to Analysis
59 views • 4 months ago
1:21:02
L1 vs "L"1, Null sets & functions, Almost Everywhere vs Norm Convergence | Intro to Analysis
66 views • 4 months ago
1:19:24
Live coding the Gambler's Problem using Value Iteration | Intro to Markov Chains and Reinforcement L
252 views • 5 months ago
1:11:13
Lebesgue Integrals 3: Absolute value of functions and series | Intro to Functional Analysis
35 views • 5 months ago
1:19:00
The Bellman Equation and 1 Player PIG solved with Value Iteration | Intro to Markov Chains and RL
169 views • 5 months ago
15:22
How far does a simple random walk go in n steps? E|X_n| = ?
777 views • 5 months ago
1:09:39
Lebesgue Integral 2: Write the function as an infinite sum of step functions | Intro to Analysis
110 views • 5 months ago
42:41
Markov Chains with actions & dice game PIG | Intro to Markov Chains and Reinforcement Learning
167 views • 5 months ago
1:17:12
Lebesgue Integral 1: Step functions & Interval Countable Additivity | Intro to Functional Analysis
83 views • 5 months ago
1:21:36
Cauchy Sequences, Complete and Banach Spaces | Intro to Functional Analysis
113 views • 5 months ago
1:19:16
Creating Markov chains by enlarging the state space & Baby Bellman Eqn | Intro Markov Chains and RL
155 views • 5 months ago
1:17:40
Closed/compact & closed ball is compact iff finite dimensional space | Intro to Functional Analysis
141 views • 5 months ago
1:12:15
Solving probabilities and expected values for Markov Chains & the (baby) Bellman Eqn | Intro to RL
453 views • 5 months ago
1:08:15
Pointwise vs L1 vs Linfinity convergence + Equivalence of norms on finite dimensional spaces | Lec 3
180 views • 5 months ago
1:16:01
Two state Markov chain example and the steady state distribution | Intro to Markov Chains Lecture 3
363 views • 5 months ago
1:13:43
Normed Vector Spaces and Function Spaces | Intro to Functional Analysis Lecture 2
170 views • 5 months ago
1:18:43
Snakes+Ladders probability problem in spreadsheet and Python | Intro to Markov Chains Lec 2
283 views • 5 months ago
1:16:23
Functions are just fancy vectors | Intro to Functional Analysis Lecture 1
628 views • 5 months ago
1:14:40
What is Reinforcement Learning? Lecture with 4 Examples | Intro to Markov Chains and RL
451 views • 5 months ago
21:05
The FAST trick to test if n is prime (with Python code) | AKS Primality Testing in poly(log n) time
1K views • 6 months ago
13:28
The Hidden Patterns of Pascal's Triangle (featuring Marc Evanstein / music.py)
1.8K views • 7 months ago
1:07:52
Intro to Data Science Lecture 22 | letter2Vec (baby names version of word2vec)
113 views • 7 months ago
1:13:01
Intro to Data Science Lecture 21 | MNIST Neural net Regularization, autoencoders, word2vec overview
198 views • 7 months ago
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