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38:17EN
Jane Street· 13 mar 2017How to Build a Reliable Exchange with Deterministic ReplayBrian Nigito · Jane StreetA matching engine, multicast and state-machine replication can turn a high-throughput exchange into a recoverable system. This talk explains the design and its tradeoffs.
25:44ENJane Street· 9 mar 2017Why Functional Programming Matters at Jane StreetSebastian Funk · Jane StreetA Jane Street developer revisits John Hughes’s classic argument and explains why expressive static types rank highest for trading systems.
28:31ENJane Street· 9 mar 2017Incremental: Self-Adjusting Computations in OCamlSebastian Funk · Jane StreetSebastian explains Jane Street’s dynamic dependency graph library and the algorithms behind efficient updates.
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3Blue1Brown· 25 nov 2016Solving the Towers of Hanoi by Counting in BinaryKeith SchwarzBinary carries select the disk to move, and a recursive argument explains why the solution uses the fewest possible moves.
16:29EN3Blue1Brown· 4 nov 2016Why Topology Matters: An Inscribed Rectangle ArgumentGrant SandersonGrant Sanderson turns pairs of points on a curve into a Möbius strip.
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Lex Fridman· 27 sept 2016PódcastFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPPresenta: Lex FridmanRichard Socher explains how word embeddings, recurrent models, GRUs, pointer mixtures, and dynamic memory networks turn language tasks into trainable end-to-end systems.
13:10EN3Blue1Brown· 1 sept 2016Why Cross-Product Coordinates Match Their GeometryGrant SandersonA linear transformation and duality connect the determinant formula to area and direction.
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GOTO Conferences· 29 ago 2016How Platforms Work: From Deployment to RecoveryCasey WestCasey West outlines six platform capabilities and demonstrates them with Cloud Foundry in 2016.
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Google DeepMind· 5 jul 2016Mustafa Suleyman’s 2016 Vision for Technology in Patient CareMustafa Suleyman · DeepMindA historical talk on clinician-led design, kidney-injury alerts, eye-scan research and the need for scrutiny.
1:09:24ENJane Street· 5 abr 2016Yaron Minsky on Effective ML: Writing OCaml for Code ReadersYaron Minsky · Jane StreetPractical lessons from Jane Street on using types, interfaces and abstraction to keep a large OCaml codebase understandable and correct.
16:01EN3Blue1Brown· 1 abr 2016The Brachistochrone: Why the Fastest Descent Is a CycloidGrant Sanderson, Steven StrogatzGrant Sanderson and Steven Strogatz explore Bernoulli’s light analogy and a geometric proof.
1:06:39ENJane Street· 31 mar 2016Why Jane Street Uses OCamlYaron Minsky · Jane StreetA Jane Street talk explains how functional programming and static types support reliable trading software, and examines the costs of choosing a less common language.
23:58ENJane Street· 31 mar 2016Effective ML: Errors, Abstraction and Managing ComplexityYaron Minsky · Jane StreetA Jane Street engineer discusses explicit failure, boilerplate, type-system restraint and the practical role of side effects.
1:04:56ENJane Street· 31 mar 2016Yaron Minsky on Incremental: From Research Idea to Production LibraryYaron Minsky · Jane StreetA history of the algorithms, memory problems and performance tradeoffs behind Jane Street’s OCaml library for self-adjusting computations.
1:12:41ENJane Street· 31 mar 2016Ron Minsky on Trading, Correctness and Jane Street’s Shift to OCamlYaron Minsky · Jane StreetA Jane Street technologist explains the market-making business and why readability, types and predictable performance shaped the firm’s choice of OCaml.
51:35ENJane Street· 31 mar 2016Yaron Minsky on Effective ML: Interfaces, Invariants and Code ReadersYaron Minsky · Jane StreetIn the first part of a 2011 Harvard lecture, Jane Street’s Yaron Minsky shows how OCaml interfaces and types can make long-lived code easier to understand and change.
52:20ENGOTO Conferences· 1 nov 2015Toyota Kata for Continuous ImprovementHåkan ForssHåkan Forss explains target conditions, coaching and small experiments.
7:27EN3Blue1Brown· 21 jun 2015A Proof of Euler’s Formula Using Graph DualityA planar graph and its dual have complementary spanning trees. Counting their edges gives a visual proof that V − E + F = 2.
1:36:30ENGoogle DeepMind· 13 may 2015Reinforcement Learning Lecture 5: Model-Free ControlDavid SilverDavid Silver explains Monte Carlo control, SARSA, eligibility traces and Q-learning.
6:13EN3Blue1Brown· 5 mar 2015Euler’s Identity as a Rotation: An Early 3Blue1Brown ExplanationA geometric introduction to how the exponential connects addition, multiplication and rotations in the complex plane.
9:47ENLex Fridman· 16 jun 2014Pódcast · 2 vocesRyan Hall on Principles and Priorities in Jiu-JitsuInvitado: Ryan Hall · Presenta: Lex FridmanA grappling instructor discusses fundamentals, details and learning.
9:16ENLex Fridman· 5 jun 2014Pódcast · 2 vocesRyan Hall on the Value of CompetitionInvitado: Ryan Hall · Presenta: Lex FridmanA martial artist discusses preparation, discipline and honest feedback.
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Lenny's PodcastPódcast · 2 vocesHard Skills, Soft Skills and Mentors: Jules Walter's Playbook for Growing as a PMInvitado: Jules Walter · Presenta: Lenny RachitskyYouTube product lead Jules Walter explains how he builds IQ and EQ skills, asks for honest feedback, and recruits mentors with the smallest possible ask.
1:00:51ENLex FridmanPódcastDeep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network FoundationsPresenta: Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.Cargar másMostrando 24 de 4485