![Ahmad Bazzi](/img/default-banner.jpg)
- Видео 175
- Просмотров 17 312 514
Ahmad Bazzi
Объединенные Арабские Эмираты
Добавлен 21 мар 2018
Ahmad Bazzi was born in Abu Dhabi, UAE. He received his Ph.D. degree in electrical engineering from EURECOM, in 2017 and his M.Sc. degree (honor role) in wireless communication systems from SUPELEC. He is a researcher with New York University (NYU) Abu Dhabi contributing to integrated sensing and communications and prior to that, he was the Algorithm and Signal Processing Team Leader at an IP intellectual company. He was awarded a CIFRE Scholarship from ANRT France, in 2014. He was nominated for Best Student Paper Award at IEEE ICASSP. He received a Silver Plate Creator Award from RUclips, for passing 100000 subscribers. He was awarded exemplary reviewer for IEEE Transactions on Communications, 2022. He was awarded exemplary reviewer for IEEE Wireless Communication Letters, 2022. He is an inventor of several patents involving intellectual property of Wi-Fi and Bluetooth products, all of which have been implemented and sold to key clients.
Business inquiries: bazziapps@gmail.com
Business inquiries: bazziapps@gmail.com
CUDA Programming for Image Processing
💡 Giveaway steps:
✅ 1. Register to NVIDIA GTC via nvda.ws/3kvUNTr
✅ 2. Wait for #GTC23 to start and join the Keynote livestream.
✅ 3. Attend GTC sessions (there’s really a lot of sessions going on - just pick one you’re interested in) 😄
✅ 4. Screenshot me a proof that you attended the keynote and a session of your choice on my email: bazziapps@gmail.com
✅ 5. Subscribe to my RUclips channel here - ruclips.net/user/ahmadbazzi 😅
✉️ Email: bazziapps@gmail.com
⏱Outline:
00:00 Intro
01:45 4080 RTX Giveaway steps
02:45 Importing numba
03:00 Importing numpy
03:21 Importing exponential from math
03:30 The CUDA JIT decorator @cuda.jit
04:21 Gaussian kernel filter for CUDA
06:02 CUDA to device
06:33 Convolutio...
✅ 1. Register to NVIDIA GTC via nvda.ws/3kvUNTr
✅ 2. Wait for #GTC23 to start and join the Keynote livestream.
✅ 3. Attend GTC sessions (there’s really a lot of sessions going on - just pick one you’re interested in) 😄
✅ 4. Screenshot me a proof that you attended the keynote and a session of your choice on my email: bazziapps@gmail.com
✅ 5. Subscribe to my RUclips channel here - ruclips.net/user/ahmadbazzi 😅
✉️ Email: bazziapps@gmail.com
⏱Outline:
00:00 Intro
01:45 4080 RTX Giveaway steps
02:45 Importing numba
03:00 Importing numpy
03:21 Importing exponential from math
03:30 The CUDA JIT decorator @cuda.jit
04:21 Gaussian kernel filter for CUDA
06:02 CUDA to device
06:33 Convolutio...
Просмотров: 162 459
Видео
Striding CUDA like i'm Johnnie Walker
Просмотров 545 тыс.Год назад
💡 Giveaway steps: ✅ 1. Register to NVIDIA GTC via nvda.ws/3kvUNTr ✅ 2. Wait for #GTC23 to start and join the Keynote livestream. ✅ 3. Attend GTC sessions (there’s really a lot of sessions going on - just pick one you’re interested in) 😄 ✅ 4. Screenshot me a proof that you attended the keynote and a session of your choice on my email: bazziapps@gmail.com ✅ 5. Subscribe to my RUclips channel here...
Symmetric Rank 1 | Exact Line Search | Theory and Python Code | Optimization Techniques #7
Просмотров 93 тыс.Год назад
In the seventh lecture, we talk about a well-known optimization technique which falls under the category of quasi Newton methods, and is called the symmetric rank 1 (SR1) algorithm. This lecture contains everything you need to know about the symmetric rank 1 optimization technique. I will show you how to use SR1 when combined with the exact line search method. The outline of this lecture is as ...
Modified Newton method | Wolfe Backtracking | Theory and Python Code | Optimization Algorithms #6
Просмотров 57 тыс.Год назад
In this one, I will show you what the modified newton algorithm is and how to use it with the backtracking search by Armijo rule. We will approach both methods from intuitive and animated perspectives. The difference between Damped and its modified newton method is that the Hessian may run into singularities at some iterations, and so we apply diagonal loading, or Tikhonov regularization at eac...
Modified Newton method | Backtracking Armijo | Theory and Python Code | Optimization Techniques #5
Просмотров 33 тыс.Год назад
In this one, I will show you what the modified newton algorithm is and how to use it with the backtracking search by Armijo rule. We will approach both methods from intuitive and animated perspectives. The difference between Damped and its modified newton method is that the Hessian may run into singularities at some iterations, and so we apply diagonal loading, or Tikhonov regularization at eac...
Modified Newton method | Exact Line Search | Theory and Python Code | Optimization Algorithms #4
Просмотров 65 тыс.Год назад
In this one, I will show you what the modified newton algorithm is and how to use it with the exact line search method. We will approach both methods from intuitive and animated perspectives. The difference between Damped and its modified newton method is that the Hessian may run into singularities at some iterations, and so we apply diagonal loading, or Tikhonov regularization at each iteratio...
Newton's method | Wolfe Condition | Theory and Python Code | Optimization Algorithms #3
Просмотров 41 тыс.Год назад
In this one, I will show you what the (damped) newton algorithm is and how to use it with the Wolfe condition for backtracking. We will approach both methods from intuitive and animated perspectives. Next, let’s talk about the line search we are going to use in this tutorial, which is based on Wolfe criterion. This is achieved by the Wolfe condition, which sufficiently decreases our function ! ...
Newton's method | Backtracking Armijo Search | Theory and Python Code | Optimization Algorithms #2
Просмотров 56 тыс.Год назад
In this one, I will show you what the (damped) newton algorithm is and how to use it with Armijo backtracking line search. We will approach both methods from intuitive and animated perspectives. Next, we talk about the line search we are going to use in this tutorial, which is the Armijo backtracking method. This is achieved by the Armijo condition, which sufficiently decreases our function ! O...
Newton's method | Exact Line Search | Theory and Python Code | Optimization Algorithms #1
Просмотров 45 тыс.Год назад
In this one, I will show you what the (damped) newton algorithm is and how to use it with the exact line search method. We will approach both methods from intuitive and animated perspectives. Context - Damped newton, just like newton’s method, makes a local quadratic approximation of the function based on information from the current point, and then jumps to the minimum of that approximation. J...
CUDA Programming on Python
Просмотров 1,2 млнГод назад
In this tutorial, I’ll show you everything you need to know about CUDA programming so that you could make use of GPU parallelization, thru simple modifications of your already existing code, running on a boring CPU. The following tutorial was recorded on NVIDIA’s Jetson Orin supercomputer. CUDA stands for Compute Unified Device Architecture, and is a parallel computing platform and application ...
I am giving away an RTX GPU by NVIDIA | World's Biggest FREE AI Conference - NVIDIA GTC Fall 2022
Просмотров 190 тыс.Год назад
Register for the event using this link: www.nvidia.com/gtc/?ncid=ref-crea-733228 NVIDIA GTC is the world's largest AI virtual conference, and it is open to the public for free. As a giveaway, one fortunate individual will receive an NVIDIA RTX 3080 Ti GPU (1199$ worth). The regulations of the giveaway are detailed in this video. #️⃣ Social Media #️⃣ 📸 Instagram: drahmadbazzi 🔊 Fa...
Quick Deploy: Object Detection via NGC on Vertex AI Workbench Google Cloud
Просмотров 93 тыс.Год назад
📚📚 About In this one, i’ll show you how to deploy one of many’s NVIDIA’s jupyter notebooks available on NGC, which in this case is object detection using TAO Detectnet on Vertex AI Workbench google cloud via NVIDIA’s new feature called Quick Deploy. For the development of AI applications on GPU-powered on-premise and cloud instances, I find that NGC catalog and Vertex AI Workbench google cloud ...
Trading crypto off Coinbase on Python | Build your trading bot to trade cryptocurrency on Coinbase
Просмотров 634 тыс.Год назад
BIND is here - bit.ly/3wczREa Github code - github.com/therealbazzi/CoinbaseProTradingBotExample 📚📚 About Trading crypto - This video shows you how to implement your own python trading bot to trade cryptocurrency on the coinbase platform. Here, I demonstrate the fundamentals of using Python and the Coinbase Pro API for algorithmic trading. To connect, I'm use the "cbpro" third-party library. Wi...
C# Tutorial from Scratch - Learn C# in less than 2 hours.
Просмотров 337 тыс.Год назад
📚📚 About In this lecture, we do an all-in-one C# tutorial. C# (pronounced "See Sharp") is a type-safe, object-oriented programming language. C# allows developers to create a wide range of safe and robust.NET applications. C# is based on the C programming language family and will be immediately known to C, C , Java, and JavaScript programmers. This tour gives an overview of the key language comp...
Pancakeswap sniping bot (all in one) python essentials for crypto trading, staking cake and more.
Просмотров 723 тыс.Год назад
📚📚 About In this video, I walk you through essentials of building your pancakeswap sniping bot (all in one) python essentials for crypto trading, staking cake and more. 🛠️🛠️ Tools Python - www.python.org/ ⏲⏲Outline 00:00 intro 00:23 what is pancakeswap ? 02:41 Update 04:30 Retrieve pancakeswap tokens 05:13 Pretty printing tokens 06:34 Search for pancakeswap token symbols 09:42 Get pancakeswap t...
The BEST & SMALLEST AI supercomputer I've ever laid hands on .. NVIDIA's Jetson AGX Orin 😍
Просмотров 395 тыс.2 года назад
The BEST & SMALLEST AI supercomputer I've ever laid hands on .. NVIDIA's Jetson AGX Orin 😍
Shannon's Capacity as a Convex Optimization Problem | Convex Optimization Application # 11
Просмотров 86 тыс.2 года назад
Shannon's Capacity as a Convex Optimization Problem | Convex Optimization Application # 11
I interviewed an AI and here’s how it went !
Просмотров 193 тыс.2 года назад
I interviewed an AI and here’s how it went !
Cryptocurrency and stock analysis through simple performance metrics, volatility, correlations etc.
Просмотров 196 тыс.2 года назад
Cryptocurrency and stock analysis through simple performance metrics, volatility, correlations etc.
Does Redis Stack change the database game? Redis with superpowers! 🚀🔥
Просмотров 525 тыс.2 года назад
Does Redis Stack change the database game? Redis with superpowers! 🚀🔥
VoiceSwap (echange de voix) par NeMo NVIDIA | L'édition française
Просмотров 47 тыс.2 года назад
VoiceSwap (echange de voix) par NeMo NVIDIA | L'édition française
Inverse Text Normalization by NVIDIA's NeMo | 3080 TI Founder's Edition Giveaway | GTC22
Просмотров 83 тыс.2 года назад
Inverse Text Normalization by NVIDIA's NeMo | 3080 TI Founder's Edition Giveaway | GTC22
Text Normalization by NVIDIA's NeMo | 3080 TI Founder's Edition Giveaway | GTC22
Просмотров 93 тыс.2 года назад
Text Normalization by NVIDIA's NeMo | 3080 TI Founder's Edition Giveaway | GTC22
Voice Swap using NVIDIA's NeMo on Python | GPU 3080 TI giveaway announcement | GTC'22
Просмотров 275 тыс.2 года назад
Voice Swap using NVIDIA's NeMo on Python | GPU 3080 TI giveaway announcement | GTC'22
How i use Notion to LaTeX my equations ^^
Просмотров 105 тыс.2 года назад
How i use Notion to LaTeX my equations ^^
Cryptocurrency headline sentiment analysis through Weights & Biases
Просмотров 168 тыс.2 года назад
Cryptocurrency headline sentiment analysis through Weights & Biases
how i use YouTube as a python OG ^^
Просмотров 240 тыс.2 года назад
how i use RUclips as a python OG ^^
Data Modeling in Redis | Creating 1-to-1, 1-to-many, and many-to-many relationships
Просмотров 117 тыс.2 года назад
Data Modeling in Redis | Creating 1-to-1, 1-to-many, and many-to-many relationships
Multidimensional Newton - Approximate nonlinear equations by sequence of linear equations - lecture6
Просмотров 134 тыс.2 года назад
Multidimensional Newton - Approximate nonlinear equations by sequence of linear equations - lecture6
I tried advanced search features of Redis in Python and here is what happened
Просмотров 1,1 млн2 года назад
I tried advanced search features of Redis in Python and here is what happened
jetson orion "super computer" 🤣🤣🤣
42:50 I'm here Plz tell me the rest of the video is just definition too 😅😅😅
I've created my cloud project but when i go to add device, i download and install the Smart Industry App but then after I scan the QR code I have no account configured basically. If i enter my Tuya Developer Account I get an error. Anyone else having this issue ? It seems that the flow has changed because Ahmad configures his coud project and after authorising the APIs that he will use he gets another window where he sets up his Project Configuration(7:47) where he sets up his account that I guess is what he logs into his Spart Industry app to link a device to his cloud app. Anybody having issues like this ?
The best I have seen on this subject so far. Thanks, Ahmed.
Can this be done between two computers and how? I tried but error 11001 occurs...
Very complicated for beginners
Make triton tutorial
Sorry for this question . But where are you from ??! I tought morocco or algeria because your surname is north african
as I begin I keep getting the warning: Empty cvx model; no action taken.
Hello Sir ! Thank you for all the explanations; is it possible to have the sheet you used for the hard margin, please ?
Very good information, thanks.
how do you calculate commission and spread ?
Hey Ahmad! Totally enjoying this video! Can you share the notebook here, so we can take a look at the whole thing at once for future reference?
If it's eventually about just this then buying a decent 4090 aren't worthy 😂
Absolutely awesome Thank you
how do i get chrome driver in windows
why rmin is 0.02 we expected it is some kind of dollars
It's just a normal nan ♫
Are there any prerequisites that should be installed before using NeMo? I followed the exact steps, but it keeps showing an error?
Sir on 6:55 why the optimal solution are [5.00-01] and [1.00+00]. ?
Thank a lot
I think there is a mistake in the push function you should increment top first then do A[top]=x
Where can I go to have a masters degree?
helpful
Great lecture, thank you
We can say that every convex combination is an affine combination but the converse is not true...
Thank you for the great series! I have some questions at 12:20 you talked about passing a posynomial through a posynomial is a generalized posynomial, however, can any generalized posynomial be represented as a posynomial of posynomials. For example, max(f1, f2) is a generalized posynomial, how can we write it as phi(f1, f2) where phi is posynomial?
is there a way to backtest with this api insted of place an actual order to test
check out our new Pancakeswap bot ruclips.net/video/TOKn1Z7KkWQ/видео.html
I wonder what is the actual equation of the blue curve you used?
all i can see is that the smile on the smiley face is convex... and the face itself is a convex set
How much size of data have you taken
thank you so much for this clear explanation
One of the RUclips gods.
Akra-Bazzi MY-Mahhhnnn!
Sir, the optmal solution provided on 26.37, in which you put warehouse transportation as 2, it gives all X1 to X6 as zero. So basically how do the units reach the warehouse from the plant?
Hello, Bazzi! At the Ex.8, shouldn't we consider the constraint \lambda >= 0? Thx!
لو في ترجمة بالعربي
it looks like it goes even faster using target = 'cpu' instead of cuda ... im also trying to do smth similar with cupy arrays and @cuda.jit but cant manage to get the code faster than cpu vectorize...
Much thanks to you sir!!!!!!!!!!!!!!!!!!!!!!!!
Thanks for your great work professor ! May I ask if it would be convenient for you to share your lecture notes?
Thanks for the smiley face Dr. Bazzi, your detailed, patient way of explaining and untangling complex abstract concepts does indeed put a smile on my face :D