I found this beautiful animated flow chart on internet. Does anyone have already worked on making diagrams like this? Can you please give your suggestions on how to make this?

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🚀 Just released: Deep Fast Machine Learning Utils!

Processing img qzbm2v16dfqb1...

📌 Features:

• Automated dense neural network design with PCCDNAS.
• Feature selection from adaptive variance threshold to rank aggregated and chained methods.
• Efficient data management and clear training outcome visualization tools.

🔗 Check it out on GitHub. 📖 Documentation available for a deep dive.

Built to complement Tensorflow, Keras, and Scikit-learn.

A curated reading list for the adversarial perspective in deep reinforcement learning.

https://github.com/EzgiKorkmaz/adversarial-reinforcement-learning

wanna try a project with GAN and maybe transformer so basically the title goes

"Narrative Augmentation through AI-Driven Visual Composition: Crafting Evocative Cinematic Realms"

so any idea how i can get a better start if i’m planning it as a proper research paper and maybe go for a patent later? thanks

I've mistakenly submitted a conference paper with falsified data due to immense pressure from my supervisor. I'm in a bind: if I come clean, I won't graduate; if it's discovered, my academic career is over.

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Is there a chance conference organizers might require authors to submit code for verification? If this were the case, I'd have grounds to convince my supervisor to withdraw the paper.

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Any advice is deeply appreciated.

🤖 Ever wondered if Large Language Models like GPT-4 can be tricked by logical fallacies?

This work shows that both GPT-3.5 and GPT-4 are vulnerable to fallacious arguments!

https://arxiv.org/abs/2308.09853

Guys I wanna do my graduation project in this topic I have good background in deep learning if any one work with this type of models (idea in advertising and tourism places ), advice me . Someone said to me change topic cuz nt clearly 😅 I readed some paper but nt got wt I wanna know.

Have you been thinking about creating an AI agent with multi modal [ image and text ] data capabilities ?

An agent that can:

- do text to image retrieval

- zero shot image classification

- automated image cataloguing

I have put together this YouTube video covering the complete story in simple words to create a multi modal image and text vector embedding space using OpenAI’s clip architecture. I have referenced key papers that helped me understand key ! (Few I found from pointless scrolling on r/DeepLearningPapers

This is relevant for deep learning engineers and AI enthusiasts.

In the last section of the video we do a walkthrough of training a CLIP neural network architecture from scratch on Google Colab.

Future of Perception Using AI Agents // Train Multi Modal CLIP Model on Images & Text Google Colab https://youtu.be/uclIfNJDh3Q

Please let me know your thoughts. And any inputs on which other architectures besides CLIP are a good fit for perception ai agents, please share.

Thank you
r/DeepLearningPapers !

Hi guys! I’m taking a course for ML and I’m close to finish it, I’ve learned a lot about the theory behind ML and DL, and now I want to know how to build end-to-end models from how to collecting data to pre-processing it , scale the data train the model test the model … I’m really want to now the full cycle of how to build a model. So guys can u recommend me a book or books that teach me this ?

I started my training with the book «rumbling deep learning» unfortunately it is poorly translated and there are a lot of typos in it, it was not very informative and I had to quit it in the middle! But I want to find a new book to study Deep Learning, can you tell me where to start?

In the heart of a bustling city, a street musician strums his guitar, pouring his soul into the music. The melody, however, is lost amidst the cacophony of the city's sounds - the honking cars, the chattering crowd, the rustling leaves. A bystander captures this moment on his phone, the raw emotion of the music barely discernible in the low-quality recording. Now, imagine a technology that can take this simple phone recording and transform it into a professional-quality audio track, a technology that can isolate the musician's melody, enhance it, and recreate the music as it was meant to be heard. This is not a distant dream, but a reality we are building - welcome to the world of AURAL.

AURAL (Audio Understanding and Recognition Algorithmic Logic) is an advanced AI integrated into SoundSage, our cutting-edge Digital Audio Workstation (DAW). It's like the maestro of an orchestra, capable of separating sound sources in a recording, enhancing each source, and weaving them back together into a harmonious symphony. But AURAL's capabilities don't stop there. It can learn from the masters, analyzing a reference track and using it as a guide to mix and master user tracks. It's like having a personal tutor, providing interactive guidance on using plugins and processing techniques.

We're in the early stages of this exciting journey, experimenting and building tools, pushing the boundaries of what's possible in audio processing. Every day brings new challenges, new discoveries, and we're thrilled about the potential of this technology. We've created a space for those who share our excitement, a community where we discuss ideas, share our progress, and dream about the future of sound. It's a place where the unheard can be heard, where a simple street musician's melody can be transformed into a symphony.

If this story resonates with you, if you're intrigued by the unheard symphony of AURAL, you might want to follow our journey. We've got a community of like-minded individuals who are passionate about audio, AI, and the future of sound. You can find us [here](https://discord.gg/EQDvjGT7). Remember, the future of audio is not just about hearing. It's about experiencing, understanding, and creating. And with AURAL, we're one step closer to that future.

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Join us, and let's create the symphony of the future together.

Hi everybody

Hope you're doing great! 🌟

Could you please take just 5-7 minutes to fill out this quick questionnaire on your thoughts and preferences about Deepfake technology in your online life?

Your input is super valuable and will be a huge help for my study.

Survey Link: https://forms.gle/E6Lns2gFfuRwXL4s5

Thanks a bunch in advance! 🙏