A collection of Deep Learning projects and resources
Join my @Prodramp YouTube Channel for all things about Data Science, machine learning and Artificial Intelligence and technology.
Join my @Prodramp YouTube Channel for all things about Data Science, machine learning and Artificial Intelligence and technology.
@Prodramp YouTube channel - Please visit YouTube channel to watch all the videos specific the GitHub content you find in this GitHub repo
- Whiteboarding - Understanding ChatGPT
- Whiteboarding - Understanding LLM Tech Stack
- Developing ChatGPT style Enterprise Content Q/A Application
- ChatGPT
- FineTune LLM
- Learning Large Language Models
- Deep Learning Study Plan MindMap
- OpenAI Whisper - Audio/Video to Text(Transcribe/Translate)
- Stable Diffusion Video - Multiple Prompts to Video
- Stable Diffusion GUI - Gradio UI for Text-to-Image TensorFlow Models
- Stable Diffusion - Text-to-Image OpenSource AI Model
- Bloom 176B Parameters - Large Language Model
- TorchStudio - Import Dataset, Train and Save Models
- EG3D - Efficient Geometry-aware 3D Generative Adversarial Networks
- Hugging Face - Model Training and Tuning, Inference, all at one place
- JoJoGAN - Face Stylization (3 Videos Series on training, inference, model export and deployment)
- 12 Research Papers to learn Text-2-Image Research
- Diffusion Models - Theory, Implemenations and Models
- All Things VQ-GAN - A 3 part video series
- Text to Image using AI Models Workshop - Step by Step Guide
- Text to Image AI Models - Different methods & different results, same target
- NeRF Scene - Instant-ngp
- LIMoE (Multimodal Mixture of Experts - Google)
- MoE (Mixture of Experts - Google)
- PyTorch Tutorials
- DALL-E Mini
- GraphViz
- Graph Neural Networks
- Topic Modeling
- Convolution Example in Python
- Self-driving Technology
- Number Series and Prediction with ML
- GPT Models (OpenAI and OpenSource)
- No More Blackbox Models: MLI or XAI
- Vision GNN: An Image is Worth Graph of Nodes
- ruDALL-E: Text 2 Image 1.3B parameters open source model
- BCI - Brain Computer Interface
- Deep Learning Rig - Installation Nvidia drivers, Cuda toolkits for Conda, TensorFlow and PyTorch
- JAX/JAXlib Installation with Cuda/cudNN
- dlib installation with Cuda, cudNN on Ubuntu 22.04 with Conda and Python
- Apple M1 with Metal GPU for Deep Learning
- If you would like to see here or need some help on similar topics, please feel free connect me at any below channels.
- 🧩 YouTube Channel: https://www.youtube.com/channel/UClLqLPWRsta-inJcDrqh6Pg
- 👀 Twitter: https://twitter.com/prodramp
- 😄 Avkash Chauhan (@avkashchauhan)
- 🌱 https://www.linkedin.com/in/avkashchauhan
- 📫 https://twitter.com/avkashchauhan
- 🕹 https://github.com/Avkash
- 📜 https://blogs.prodramp.com/
- https://github.com/eriklindernoren/ML-From-Scratch
- https://github.com/kwea123/nerf_pl#blender
- https://github.com/bmild/nerf
- https://github.com/musikalkemist/pytorchforaudio
- https://medium.com/@oleguer.canal/the-attention-mechanism-zoo-309c05768ed9
- https://towardsdatascience.com/audio-deep-learning-made-simple-part-1-state-of-the-art-techniques-da1d3dff2504
- https://github.com/RizwanMunawar/yolov7-pose-estimation
- https://github.com/ultralytics/yolov5
- https://www.augmentedstartups.com/yolox-pro-computer-vision-dashboard
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