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Here, we create a convolutional neural network using the same neural network that we used in the machine learning tutorial series: https://pythonprogramming.net/....tflearn-machine-lear
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Adding logic to the Starcraft 2 artificial intelligence to defend our main base.
Text-based tutorial: https://pythonprogramming.net/....defending-python-sc2
Asyncio basics: https://pythonprogramming.net/....asyncio-basics-inter
Neural Networks from Scratch book: https://nnfs.io
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Welcome to part 8 of the Deep Learning with Python, Keras, and Tensorflow series. In this tutorial, we're going to work on using a recurrent neural network to predict against a time-series dataset, which is going to be cryptocurrency prices.
Text tutorials and sample code: https://pythonprogramming.net/....cryptocurrency-recur
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In the previous tutorial, we covered how to use channels to send and receive values with goroutines. That said, it was just a basic example. In reality, we're likely to have questions of synchronization and iterating through known, or unknown, numbers of channel returns.
Text tutorials and sample code: https://pythonprogramming.net/go/
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Welcome to the next part of our Deep Learning with Python, TensorFlow, and Keras tutorial series. In this tutorial, we're going to continue building our cryptocurrency-price-predicting Recurrent Neural Network.
Text tutorials and sample code: https://pythonprogramming.net/....balancing-rnn-data-d
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A self-driving car in GTA 5.
For more information on this project, and how it all began from simple lane detection to deep learning, follow the full tutorial series here: https://pythonprogramming.net/....game-frames-open-cv-
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Welcome to the next tutorial covering deep learning with Python, Tensorflow, and Keras. We've been working on a cryptocurrency price movement prediction recurrent neural network, focusing mainly on the pre-processing that we've got to do. In this tutorial, we're going to be finishing up by building our model and training it.
Text tutorials and sample code: https://pythonprogramming.net/....crypto-rnn-model-dee
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Welcome to a tutorial on sockets with Python 3. We have a lot to cover, so let's just jump right in. The socket library is a part of the standard library, so you already have it.
Source code and text-based tutorial: https://pythonprogramming.net/....sockets-tutorial-pyt
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DreamFusion is Google research (https://arxiv.org/pdf/2209.14988.pdf) into generating 3D objects from text prompts, and is based off 2D diffusion models.
Stable DreamFusion github: https://github.com/ashawkey/st....able-dreamfusion?s=0
NeRF (Neural Radiance Fields): https://www.matthewtancik.com/nerf
Meta AI make-a-video: https://makeavideo.studio/
Neural Networks from Scratch book: https://nnfs.io
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Downloading and installing Python 3, along with an editor and writing our very first, though super basic, program!
Playlist: https://www.youtube.com/playli....st?list=PLQVvvaa0QuD
#python #programming #tutorial
Welcome to a reinforcement learning tutorial. In this part, we're going to focus on Q-Learning.
Q-Learning is a model-free form of machine learning, in the sense that the AI "agent" does not need to know or have a model of the environment that it will be in. The same algorithm can be used across a variety of environments.
For a given environment, everything is broken down into "states" and "actions." The states are observations and samplings that we pull from the environment, and the actions are the choices the agent has made based on the observation. For the purposes of the rest of this tutorial, we'll use the context of our environment to exemplify how this works.
Text-based tutorial and sample code: https://pythonprogramming.net/....q-learning-reinforce
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Using Python to Play Cyberpunk 2077 through computer vision.
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Basic Raspberry Pi Robot Car Playlist: http://www.youtube.com/watch?v=LlFkybEQFFA&list=PLQVvvaa0QuDeJlgD1RX9_49tMLUxvIxF4&feature=share
Greetings and welcome to the second part of our robotics with python and the raspberry pi! In this video, the basic assembly is shown for how to hook up our pi to the l298n controller, battery pack, and motors.
After the initial hooking up, you are shown an extremely basic python script that will make the motor run momentarily and then stop. As we continue, we will build slightly more complex code, and get the motors to work with each other.
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An actually-open-AI model is available for you to download the weights to and tinker with, GPT-J. It's a 6 billion parameter large language model that can do long-form natural language generation, do programming, be a chatbot, do translations, and much more.
GPT-J Text examples: https://pythonprogramming.net/....GPT-J-6b-parm-transf
GPT-J Github: https://github.com/kingoflolz/mesh-transformer-jax
The Pile paper: https://arxiv.org/pdf/2101.00027.pdf
GPT-J Web demo: https://6b.eleuther.ai/
EleutherAI: https://www.eleuther.ai/
Multimodal Few-Shot Learning with
Frozen Language Models: https://arxiv.org/pdf/2106.13884.pdf
Neural Networks from Scratch book: https://nnfs.io
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Exploring a couple of the latest text to image generators that you can begin using right now, Stable Diffusion and MidJourney.
Stable Diffusion model download: https://huggingface.co/CompVis..../stable-diffusion-v1
MidJourney website: https://www.midjourney.com/home/
BLOOM AI model video: https://www.youtube.com/watch?v=3EjtHs_lXnk
DreamStudio: https://beta.dreamstudio.ai
Neural Networks from Scratch book: https://nnfs.io
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Working on a chatbot that you can speak to with your microphone and that responds via your speakers.
Part 2: https://youtu.be/lheXIYXanuU
Setting up and checking out jarvis: https://youtu.be/fQzjgaKSrkc
DialoGPT large: https://huggingface.co/microsoft/DialoGPT-large
Learn more about NVIDIA Jarvis: https://nvda.ws/2QC3NYv
See more of the DGX Station A100 here: https://youtu.be/0mAesfFt4us
Neural Networks from Scratch book: https://nnfs.io
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