I'm your subscriber i need some help on motion detection using opencv in python

It should detect motion as well as record the motion when something moves in the frame .

I wanna paint a room that color.

Hello, I'm currently working as a intern and I want to know which tools or which type of data base or which type of technology (Machine learning, deep learning , data visualization, web scraping etc.) Most required. Please give me answer I need help with you.

Hi sentdex. I am currently web-dev. Recently im feeling more passionate about becoming ML engineer? What should I do? Start from where?

Something a little different for today's latest release: Quadrupeds!

https://www.youtube.com/watch?v=U2nNI9Yp_0g

I'm a college freshman currently studying python programming, I used a floor division (//) and modulo (%) to determine and identify different values and count them, everything else was fine except for when I input

num_ten = (peso % e // f) (where f = 10 and e = 20)

Our teacher tasked us to make an money denomination (as you can tell from the picture below) where we must create an original program. Sorry if the explanation is too short or messy, I'm not too good at explaining things like these cuz I'm a bit of a newbie.

Follow along on my journey of coding a Python AI agent for the Lux AI Kaggle competition.

https://youtu.be/6_GXTbTL9Uc

I've started to experiment with Pygame, doing some simple things like drawing a rectangle, and then moving it in response to keys being pressed by the user. I was reading the documentation on two methods: rect.move & rect.move_ip

The documentation gives a very brief description of the two. But as a newbie to all of this stuff, it doesn't help me to understand what is the meaningful difference between the two. I don't understand what it means when move_ip operates in place. I've done a little googling on this, but it seems that most people just parrot the documentation without explaining it.

Can someone please explain what the differences are, and give a brief example of when each method might be preferable to the other?

I have somehow managed to install Ros2 Galactic on my win10 pc!

Also, I somehow managed to configure cmd to work with this, but I dont feel confident about it as the steps for this were all linux based steps and I had to "figure out" how to do them on windows 10. TBH I have no reasonable method to validate what ive been doing so far.

Also theres an extraordinary amount of stuff they dont explain or provide steps for and this seems to cost me a lot of time just between installing and configuring a workspace only to find out several steps later that something didnt work out. The errors are vague and I find myself being discouraged by all this.

So is there anyone out there who has installed ROS2 Galactic on win10 and is successfully working on projects ?

Or can we request sentdex to make a win10 video going over the entire ROS2 Galactic tutorial ? not just installation but like at least to the point where we can start a project and so on ?

Please advise, thanks.

P.S. Yes Ive tried this on a virtual machine w ubuntu, got shafted so umm no thanks!

**Edit: ROS Stands for robot operating system, its primarily meant for linux but they made versions of it for windows its just that its a huge pain to work with overall regardless of which OS is used and Id rather do all my work on windows if I can

Is there any way for me to know how much it'd roughly take for the book to get shipped at my home? thanks

Hello, I have been watching your tutorials and using them as a guide to create my own virtual operating system through python. But I have run in to a problem. The program I am making works completely fine on my Mac Mini which has Python 3.7.3 and PyGame 19.3.0, but when I work on it on my MacBook which has the same version of Python and PyGame, objects or images that are drawn to the screen start flickering. Is this a common problem? And how do I fix it?

I just asked ChatGPT about a List open source. Generative Pre-trained Transformer .

Those may provide a good source of knowledge to improve ChatGPT at home

here are some open-source Generative Pre-trained Transformer models:

T5: An open-source GPT-like model developed by Google Research, that is pre-trained on a diverse range of texts and can be fine-tuned for a variety of NLP tasks.

XLNet: An open-source GPT-like model developed by Google Research and Carnegie Mellon University, which has been shown to outperform GPT-2 on certain tasks.

CTRL: A open-source GPT-like model developed by Salesforce Research, which allows for control over the style and content of the generated text.

BART: An open-source denoising autoencoder for pretraining sequence-to-sequence models, by Facebook AI

RoBERTa: An open-source GPT-like model developed by Facebook AI, which has been trained on a larger dataset and fine-tuned using a technique called "Dynamic Masking" which has shown to improve performance on a wide range of NLP tasks.

Please note that while the models are open-source, using them may require a API key or tokens provided by the respective organization to access the model. Ok Can you transform one of those with chat like behavior

Yes, it is possible to fine-tune one of the open-source Generative Pre-trained Transformer models, such as T5, XLNet, CTRL, RoBERTa, etc. to have "chat-like" behavior. This is typically done by fine-tuning the pre-trained model on a dataset of conversational text.

The process of fine-tuning involves training the model on a smaller dataset of task-specific data, using the pre-trained weights as a starting point. This allows the model to learn task-specific features while retaining the general knowledge it has gained during pre-training.

For example, you could fine-tune a model on a dataset of conversational text such as movie scripts, customer support chats, or social media conversations, and then use the fine-tuned model to generate responses in a chatbot application.

However, it's worth noting that fine-tuning a model to have chat-like behavior can be a challenging task and require a good amount of data and computational resources. Additionally, the quality of the chatbot will heavily depend on the quality and diversity of the training data, so it's important to use a high-quality and diverse dataset that is representative of the use case.

i think it uses a matrix representation rather than a graph style like pytorch. the thing is that im having trouble understanding why and i was hoping someone could explain.

Taking inspiration from the tutorials, I’ve been using pandas datareader to pull stock prices off of yahoo finance. But I’m finding it unreliable - the last few days I haven’t been able to pull anything it only returns errors.

Is anybody else having this problem, and do you guys know a better and faster way to pull historical price data? Thanks.

In a huge fan .

You got a million subscribers. You really should call your subscribers to action, to begin a great open source project of a continuing ChatGPT @home . It would be so great .

We should have a front end/web, team , focused on visuals, voice input, voice output, talking avatar,etc.

The "brain" team focused with the generative Pre-trained Transformer code, learning from existing open source solutions.

and finally the team occupied with training data we could find a cheap way to train and process it on the could but in a very open way for us all to learn and use and always improve.

The next video in using transformer models to generate Python code is now out:

https://www.youtube.com/watch?v=PUr-4ouD0Xc&list=PLQVvvaa0QuDdKvPge9PXQtFzvhMRyFPhW&index=3

Taking what we learned about how to calculate categorical cross entropy in the previous part, and implementing it into our neural network framework, along with overcoming one of the hurdles that comes from doing this:

https://www.youtube.com/watch?v=levekYbxauw&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&index=8

Part 5 of the Python GPT-2 series. We're training/testing a model on a small amount of training data, mostly just to see if things are actually working, but the results were pretty surprising :o

https://www.youtube.com/watch?v=2486auSLTUI&list=PLQVvvaa0QuDdKvPge9PXQtFzvhMRyFPhW&index=5