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630 results

Steve Brunton
Applications of Optimization

Here we provide a high-level overview of some of the applications of optimization in modern machine learning, physics, and ...

25:23
Applications of Optimization

11,320 views

2 days ago

Sir Explains
Solving Optimisation (Maximum/Minimum) Problems - Only Product Rule

In this video, I cover how to solve optimisation problems, involving both maxima, minima, and sign test techniques. If you have any ...

26:27
Solving Optimisation (Maximum/Minimum) Problems - Only Product Rule

0 views

1 day ago

CppNow
Keynote: Benchmarking - It's About Time - Matt Godbolt - C++Now 2026

https://www.cppnow.org​ --- Keynote: Benchmarking - It's About Time - Matt Godbolt - C++Now 2026 --- Every low-latency C++ ...

1:37:32
Keynote: Benchmarking - It's About Time - Matt Godbolt - C++Now 2026

4,562 views

3 days ago

Geometry, Algebra and Physics Seminar at KIAS
[GAP] Geordie Williamson: Can we describe canonical bases as the solutions of optimization problems?

Geometry, Algebra and Physics Seminar at KIAS https://sites.google.com/view/gapkias hosted by Hyun Kyu Kim, at KIAS (Korea ...

1:22:44
[GAP] Geordie Williamson: Can we describe canonical bases as the solutions of optimization problems?

24 views

4 days ago

Clymetime
3.5 Content: Optimizing Volume

In this video, we will be going through a classic optimization problem. We will be going through each one of the steps for ...

25:33
3.5 Content: Optimizing Volume

3 views

1 day ago

Voyager
The Million Dollar Problem No One Can Solve

If you find this work valuable, subscribing or becoming a member on Patreon goes a long way in supporting the channel.

28:40
The Million Dollar Problem No One Can Solve

21,533 views

3 days ago

Learning Bayesian Statistics
#161 Amortized Inference & Neural Processes, with Luigi Acerbi

Support & Resources → Support the show on Patreon: https://www.patreon.com/c/learnbayesstats → Bayesian Modeling Course ...

1:32:15
#161 Amortized Inference & Neural Processes, with Luigi Acerbi

80 views

1 day ago

Mixed Integer Programming
Building Cost Function Approximations for Sequential Decision Problems in Python

A Cost Function Approximation (CFA) is one of the four policies of Sequential Decision Analytics proposed by Prof. Warren Powell ...

55:24
Building Cost Function Approximations for Sequential Decision Problems in Python

177 views

4 days ago

Microsoft Fabric
DP-700 Part 3: Monitor and Optimize Solutions

Welcome to the third episode of Get Certified: DP-700 Fabric Data Engineer (accelerated). Discover how to monitor and fine-tune ...

1:04:55
DP-700 Part 3: Monitor and Optimize Solutions

41 views

1 day ago

Optimization City
Mastering Stochastic Dynamic Programming | Theory + Fully Solved Problems

Welcome to this comprehensive and beginner‑friendly tutorial on Stochastic Dynamic Programming (SDP). In this video, we ...

40:10
Mastering Stochastic Dynamic Programming | Theory + Fully Solved Problems

6 views

4 days ago

NPTEL-NOC IITM
Image rejection

"Concept of image and problems associated with it, approaches for image rejection, attenuating out-of-band signals to a certain ...

1:00:27
Image rejection

557 views

4 days ago

LimitXToIIT
Maxima & Minima | Complete Theory + Problem Solving | JEE Maths

In this lecture, you'll build a strong conceptual foundation and learn how to solve a wide variety of optimization problems with ...

1:49:43
Maxima & Minima | Complete Theory + Problem Solving | JEE Maths

17 views

4 days ago

Emmanuel Jesuyon Dansu
20. Why Neural Networks Keep Improving Instead of Randomly Guessing

In this lesson, we explore why neural networks improve over time instead of making random guesses by examining optimization ...

37:51
20. Why Neural Networks Keep Improving Instead of Randomly Guessing

21 views

1 day ago

thebasics.academy
The Wrong Data Structure Cost Me 20 Minutes | LeetCode 1456

I tackled LeetCode 1456 — Maximum Number of Vowels in a Substring of Given Length — and immediately overcomplicated it by ...

1:04:45
The Wrong Data Structure Cost Me 20 Minutes | LeetCode 1456

0 views

7 days ago

Arena AI
Beyond LLM routing: a new way to optimize agent pipelines

Melissa Pan, a PhD candidate at UC Berkeley's Sky Computing Lab, walks through her research on dynamically selecting the ...

30:38
Beyond LLM routing: a new way to optimize agent pipelines

2,792 views

4 days ago

Sunny Savita
GRPO Fine-Tuning with Practical | DeepSeekMath, PPO vs GRPO, Hugging Face & Unsloth

Learn GRPO (Group Relative Policy Optimization) from scratch and fine-tune an LLM using Hugging Face TRL and Unsloth.

47:12
GRPO Fine-Tuning with Practical | DeepSeekMath, PPO vs GRPO, Hugging Face & Unsloth

366 views

2 days ago

Emmanuel Jesuyon Dansu
19. The Most Important Algorithm in Deep Learning

In this lesson, you will master Gradient Descent, the most important optimization algorithm in deep learning. Starting from the ...

50:21
19. The Most Important Algorithm in Deep Learning

22 views

1 day ago

Uruguay OC
🚨 Having Issues with NVIDIA Drivers? Watch This Before Blaming the Driver

🚨 Having trouble with NVIDIA drivers? Before blaming the driver, there's something you should check. In this video, I explain ...

32:31
🚨 Having Issues with NVIDIA Drivers? Watch This Before Blaming the Driver

2,442 views

2 days ago

Think Stack
Dynamic Programming: Beginner to Advanced (Part-1) 🚀

Dynamic Programming: Beginner to Advanced(Part-1) Dynamic Programming (DP) is one of the most powerful problem-solving ...

27:50
Dynamic Programming: Beginner to Advanced (Part-1) 🚀

6 views

6 days ago

C60 AI
The Future of Ready Mix Decision Making Is Here

See how ask C60 and C60 AI Agents help producers move beyond reporting and into AI-powered margin optimization.

58:27
The Future of Ready Mix Decision Making Is Here

7 views

1 day ago