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1,938 results

Topos Institute
[2-torial] David Jaz tells Brendan about a topos-theoretic interpretation for conceptual modelling

Recorded at the Oxford Office on the 5th of December 2025.

1:24:47
[2-torial] David Jaz tells Brendan about a topos-theoretic interpretation for conceptual modelling

400 views

4 weeks ago

Decoding Complexities
How to Fit Curves using Linear Regression (Feature Engineering)

Linear Regression is powerful, but it has a fatal flaw: it assumes the world is a straight line. But real-world data is curvy, messy, ...

6:19
How to Fit Curves using Linear Regression (Feature Engineering)

41 views

4 weeks ago

media.ccc.de
39C3 - How To Minimize Bugs in Cryptography Code

https://media.ccc.de/v/39c3-how-to-minimize-bugs-in-cryptography-code "Don't roll your own crypto" is an often-repeated ...

40:04
39C3 - How To Minimize Bugs in Cryptography Code

4,058 views

2 days ago

iMerit
Ango Deep Reasoning Lab For Advance Math

In this demo, we show how iMerit's Ango Hub Deep Reasoning Lab helps improve large language models on advanced math and ...

3:48
Ango Deep Reasoning Lab For Advance Math

67 views

4 weeks ago

NeuralNine
Linear Regression From Scratch in Python (Mathematical, Closed-Form)

Today we implement Linear Regression from scratch in Python using the closed-form solution. We first cover the mathematical ...

27:26
Linear Regression From Scratch in Python (Mathematical, Closed-Form)

4,196 views

7 days ago

IBM Technology
AI Code Generation: Wins, Fails and the Future

Explore the podcast → https://ibm.biz/Bdbw6n What's the future of AI code generation? This week on Mixture of Experts, host Tim ...

35:19
AI Code Generation: Wins, Fails and the Future

11,811 views

2 weeks ago

Daniel Bourke
End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo)

In this video we fully fine-tune Google's Gemma 3 270M Small Language Model to do structured data extraction. Because the ...

59:49
End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo)

3,452 views

1 day ago

CosmoX
Make Large Language Models 4× Faster! Jacobi Forcing for Causal Parallel Decoding Explained

Explore the cutting-edge paper “Fast and Accurate Causal Parallel Decoding using Jacobi Forcing”! This video breaks down a ...

1:47
Make Large Language Models 4× Faster! Jacobi Forcing for Causal Parallel Decoding Explained

6 views

3 weeks ago

Codeminer42
How my models work: Loading, optimization and execution

In this brownbag, Beatriz will present how the inference process of AI models works — from loading the weights to generating ...

27:01
How my models work: Loading, optimization and execution

97 views

Streamed 4 weeks ago

The Julia Programming Language
QUBO.jl | Maciel Xavier | JuliaCon Global 2025

QUBO.jl by Pedro Maciel Xavier PreTalx: https://pretalx.com/juliacon-2025/talk/BY7RM7/ Quantum algorithms and devices are ...

14:43
QUBO.jl | Maciel Xavier | JuliaCon Global 2025

264 views

1 month ago

Reinike AI
How NVIDIA’s 8B Model Beat GPT-5 Using Reinforcement Learning

NVIDIA just changed the game for AI Agents. Their new paper, ToolOrchestra, proves you don't need a trillion-parameter model ...

7:38
How NVIDIA’s 8B Model Beat GPT-5 Using Reinforcement Learning

4,768 views

1 month ago

vlogommentary
Passing Extra Parameters to scipy.optimize.curve_fit for Piecewise Functions

Learn how to supply additional parameters to a piecewise fitting function in SciPy's curve_fit without altering its signature.

2:17
Passing Extra Parameters to scipy.optimize.curve_fit for Piecewise Functions

0 views

3 weeks ago

Sensmetry
Lesson 23 -  Formal Requirements, Constraints and Templates | Advent of SysML v2

Welcome to Day 23 of Advent of SysML v2! In today's video, we continue looking at requirements, adding precision with formal ...

4:51
Lesson 23 - Formal Requirements, Constraints and Templates | Advent of SysML v2

118 views

2 weeks ago

PyData Venice
PyDataVE #24 - #MachineLearning edition

We'll have two interesting sessions in English : Árpád Goretity and Oliver Kocsis will talk to us about #NPL solutions and ...

1:18:01
PyDataVE #24 - #MachineLearning edition

72 views

Streamed 3 weeks ago

Mathieu Torchia
The "Model" Buzzword: What It Is & Why You'll Finally Understand AI

Are you tired of feeling confused every time someone mentions "Machine Learning Models" or "AI Algorithms"? This is the ...

6:57
The "Model" Buzzword: What It Is & Why You'll Finally Understand AI

64 views

4 weeks ago

Ai Guru
Backpropagation to Word Embeddings - Dropout, Regularization, N-grams, Word2Vec, Language Model

AIML Lecture Series : https://www.youtube.com/playlist?list=PLMIHypEMTeA9GK8RgT-OlJ-BK29vDMf8n AI Math and ...

37:20
Backpropagation to Word Embeddings - Dropout, Regularization, N-grams, Word2Vec, Language Model

124 views

2 weeks ago

INI Seminar Room 1
MESW02 | Prof. Andy Philpott | Long-term generation capacity expansion models in JuDGE

MESW02 | Prof. Andy Philpott | Long-term generation capacity expansion models in JuDGE Speaker: Professor Andy Philpott ...

44:55
MESW02 | Prof. Andy Philpott | Long-term generation capacity expansion models in JuDGE

0 views

3 weeks ago

Growing Science
Sequencing

This video shows how to formulate a sequencing problem using mixed integer programming. The model is useful for ...

4:46
Sequencing

0 views

10 days ago

HYPOTHALAMUS Ai
RCADT - GAMS Environment

HYPOTHALAMUS Artificial Intelligence, HAI DIGITAL TRANSFORMATION WITH ARTIFICIAL INTELLIGENCE AND REAL-TIME ...

30:05
RCADT - GAMS Environment

0 views

10 days ago

AI Engineer
DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners

Applications developed for the enterprise need to be rigorous, testable, and robust. The same is true for applications that use AI, ...

1:13:13
DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners

15,732 views

1 day ago