CNN-Filter-DB
AI-For-Beginners
| CNN-Filter-DB | AI-For-Beginners | |
|---|---|---|
| 1 | 8 | |
| 28 | 31,684 | |
| - | 4.3% | |
| 2.2 | 6.7 | |
| 11 months ago | 4 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Creative Commons Attribution Share Alike 4.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CNN-Filter-DB
-
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters (CVPR 2022 Oral)
Repo & dataset: https://github.com/paulgavrikov/CNN-Filter-DB
AI-For-Beginners
-
FREE AI Course By Microsoft: ZERO to HERO! 🔥
🔗 https://github.com/microsoft/AI-For-Beginners 🔗 https://microsoft.github.io/AI-For-Beginners/
- AI For Beginners
-
Artificial Intelligence for Beginners – A Curriculum
This is a good summary of most topics in AI/ML. The only thing that it seems to by missing (or maybe I'm just not seeing it) is a section on generative AI for images and video (DALL-E, Stable Diffusion etc).
They do cover LLMs which is generative AI for text though: https://github.com/microsoft/AI-For-Beginners/blob/main/less...
- Artificial Intelligence course
- Artificial Intelligence for Beginners course
- Microsoft's AI for Beginners
-
Announcing a New Free Curriculum: Artificial Intelligence for Beginners
Students can use this curriculum to learn the basics of AI and Neural Networks. In addition to text-based lessons, there are executable Jupyter Notebooks with samples, as well as labs that you can do to deepen your knowledge. You can run notebooks either on your local computer or in the cloud. Join your peers on GitHub Discussion Boards to learn together and watch for more learning opportunities online.
What are some alternatives?
Food-Recipe-CNN - food image to recipe with deep convolutional neural networks.
GAN-RNN_Timeseries-imputation - Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle.
GTSRB - Convolutional Neural Network for German Traffic Sign Recognition Benchmark
DeepLearning - Contains all my works, references for deep learning
diffae - Official implementation of Diffusion Autoencoders
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).