{"id":21161306,"url":"https://github.com/the-ai-summer/learn-deep-learning","last_synced_at":"2025-07-09T14:31:24.819Z","repository":{"id":41401023,"uuid":"384878764","full_name":"The-AI-Summer/learn-deep-learning","owner":"The-AI-Summer","description":"AI Summer's complete catalog of articles","archived":false,"fork":false,"pushed_at":"2021-12-30T09:52:19.000Z","size":1286,"stargazers_count":107,"open_issues_count":0,"forks_count":25,"subscribers_count":5,"default_branch":"main","last_synced_at":"2024-04-09T03:26:40.208Z","etag":null,"topics":["computer-vision","data-science","deep-learning","deep-neural-networks","machine-learning","natural-language-processing"],"latest_commit_sha":null,"homepage":"https://theaisummer.com/","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n\u003cdiv align=\"center\"\u003e\n\u003cimg  src=\"https://theaisummer.com/static/cdd4b958f811f0af03208dbdd27809c3/69585/logo_large.png\"\u003e\n\u003cbr\u003e\n\u003c/div\u003e\n\n\u003cbr\u003e\n\n\u003cdiv align=\"center\"\u003e\n    \u003ca target=\"_blank\" href=\"https://www.linkedin.com/company/ai-summer/\"\u003e\u003cimg src=\"https://img.shields.io/badge/style--5eba00.svg?label=LinkedIn\u0026logo=linkedin\u0026style=social\"\u003e\u003c/a\u003e\u0026nbsp;\n    \u003ca target=\"_blank\" href=\"https://www.twitter.com/theaisummer\"\u003e\u003cimg src=\"https://img.shields.io/twitter/follow/theaisummer?label=%20Follow\u0026style=social\"\u003e\u003c/a\u003e\u0026nbsp;\n  \u003ca target=\"_blank\" href=\"https://discord.gg/2ezWq3r5hv\"\u003e\u003cimg src=\"https://img.shields.io/badge/Discord-lightgrey?style=flat\u0026logo=discord\"\u003e\u003c/a\u003e\u0026nbsp;\n    \u003cbr\u003e\n\u003c/div\u003e\n\n\u003cbr\u003e\n\n\n# Learn Deep Learning with AI Summer\n\nA collection of all articles (almost 100) written for the AI Summer blog organized by topic.\n\n## Deep Learning Theory\n\n### Machine Learning\n\n- [A journey into Optimization algorithms for Deep Neural Networks](https://theaisummer.com/optimization/)\n- [Regularization techniques for training deep neural networks](https://theaisummer.com/regularization/)\n- [In-layer normalization techniques for training very deep neural networks](https://theaisummer.com/normalization/)\n- [Explainable AI (XAI): A survey of recents methods, applications and frameworks](https://theaisummer.com/xai/)\n- [Spiking Neural Networks: where neuroscience meets artificial intelligenc](https://theaisummer.com/spiking-neural-networks/)\n\n### Convolutional Neural Networks\n\n- [Best deep CNN architectures and their principles: from AlexNet to EfficientNet](https://theaisummer.com/cnn-architectures/)\n- [Intuitive Explanation of Skip Connections in Deep Learning](https://theaisummer.com/skip-connections/)\n- [Understanding the receptive field of deep convolutional networks](https://theaisummer.com/receptive-field/)\n\n### Recurrent Neural Networks\n\n- [Recurrent neural networks: building a custom LSTM cell](https://theaisummer.com/understanding-lstm/) ([colab](https://colab.research.google.com/drive/1Rb8OiF-AZ_Y3uFj1O2S0IyocFMhHoTCV?usp=sharing) / [repo](https://github.com/The-AI-Summer/RNN_tutorial))\n- [Recurrent Neural Networks: building GRU cells VS LSTM cells in Pytorch](https://theaisummer.com/gru/)\n- [Predict Bitcoin price with Long sort term memory Networks (LSTM)](https://theaisummer.com/Bitcon_prediction_LSTM/)\n\n### Autoencoders\n\n- [How to Generate Images using Autoencoders](https://theaisummer.com/Autoencoder/)\n- [The theory behind Latent Variable Models: formulating a Variational Autoencoder](https://theaisummer.com/latent-variable-models/)\n\n### Generative Adversarial Networks\n\n- [Decrypt Generative Adversarial Networks (GAN)](https://theaisummer.com/Generative_Artificial_Intelligence/)\n- [GANs in computer vision - Introduction to generative learning](https://theaisummer.com/gan-computer-vision/) ([repo](https://github.com/The-AI-Summer/GANs-in-Computer-Vision))\n- [GANs in computer vision - Conditional image synthesis and 3D object generation](https://theaisummer.com/gan-computer-vision-object-generation/)\n- [GANs in computer vision - Improved training with Wasserstein distance, game theory control and progressively growing schemes](https://theaisummer.com/gan-computer-vision-incremental-training/)\n- [GANs in computer vision - 2K image and video synthesis, and large-scale class-conditional image generation](https://theaisummer.com/gan-computer-vision-video-synthesis/)\n- [GANs in computer vision - self-supervised adversarial training and high-resolution image synthesis with style incorporation](https://theaisummer.com/gan-computer-vision-style-gan/)\n- [GANs in computer vision - semantic image synthesis and learning a generative model from a single image](https://theaisummer.com/gan-computer-vision-semantic-synthesis/)\n\n### Attention and Transformers\n\n- [How Attention works in Deep Learning: understanding the attention mechanism in sequence models](https://theaisummer.com/attention/)\n- [How Transformers work in deep learning and NLP: an intuitive introduction](https://theaisummer.com/transformer/)\n- [How the Vision Transformer (ViT) works in 10 minutes: an image is worth 16x16 words](https://theaisummer.com/vision-transformer/)\n- [How Positional Embeddings work in Self-Attention (code in Pytorch)](https://theaisummer.com/positional-embeddings/)\n- [Why multi-head self attention works: math, intuitions and 10+1 hidden insights](https://theaisummer.com/self-attention/)\n- [Transformers in computer vision: ViT architectures, tips, tricks and improvements](https://theaisummer.com/transformers-computer-vision/)\n\n### Graph Neural Networks\n\n- [Graph Neural Networks - An overview](https://theaisummer.com/Graph_Neural_Networks/)\n- [How Graph Neural Networks (GNN) work: introduction to graph convolutions from scratch](https://theaisummer.com/graph-convolutional-networks/) ([colab](https://colab.research.google.com/drive/1mMUKnvM_Byu8wEcJpFSYGnniPPhIOD7N?usp=sharing))\n- [Best Graph Neural Network architectures: GCN, GAT, MPNN and more](https://theaisummer.com/gnn-architectures/)\n\n### Self-supervised Learning\n\n- [Grokking self-supervised (representation) learning: how it works in computer vision and why](https://theaisummer.com/self-supervised-representation-learning-computer-vision/)\n- [Self-supervised representation learning on videos](https://theaisummer.com/self-supervised-learning-videos/)\n- [Understanding SWAV: self-supervised learning with contrasting cluster assignments](https://theaisummer.com/swav/)\n\n### Reinforcement Learning\n\n- [The secrets behind Reinforcement Learning](https://theaisummer.com/Reinforcement_learning/)\n- [Deep Q Learning and Deep Q Networks](https://theaisummer.com/Deep_Q_Learning/)\n- [Q-targets, Double DQN and Dueling DQN](https://theaisummer.com/Taking_Deep_Q_Networks_a_step_further/)\n- [Unravel Policy Gradients and REINFORCE](https://theaisummer.com/Policy-Gradients/)\n- [The idea behind Actor-Critics and how A2C and A3C improve them](https://theaisummer.com/Actor_critics/)\n- [Trust Region and Proximal policy optimization (TRPO and PPO)](https://theaisummer.com/TRPO_PPO/)\n\n## Deep Learning Applications\n\n### Image segmentation\n\n- [An overview of Unet architectures for semantic segmentation and biomedical image segmentation](https://theaisummer.com/unet-architectures/)\n- [Semantic Segmentation in the era of Neural Networks](https://theaisummer.com/Semantic_Segmentation/)\n\n### Object detection\n\n- [Localization and Object Detection with Deep Learning](https://theaisummer.com/Localization_and_Object_Detection/)\n- [YOLO - You only look once (Single shot detectors)](https://theaisummer.com/YOLO/)\n\n### Human pose estimation\n\n- [Human Pose Estimation](https://theaisummer.com/Human-Pose-Estimation/)\n\n### Face synthesis\n\n- [A closer look on Deepfakes: face sythesis with StyleGAN, face swap with XceptionNet and facial attributes and expression manipulation with StarGAN](https://theaisummer.com/deepfakes/)\n\n### Recommendation systems\n\n- [An introduction to Recommendation Systems: an overview of machine and deep learning architectures](https://theaisummer.com/recommendation-systems/)\n\n### Autonomous cars\n\n- [Self-driving cars using Deep Learning](https://theaisummer.com/Self_driving_cars/)\n\n### Medical imaging\n\n- [Deep learning in medical imaging - 3D medical image segmentation with PyTorch](https://theaisummer.com/medical-image-deep-learning/) ([repo](https://github.com/black0017/MedicalZooPytorch))\n- [Understanding coordinate systems and DICOM for deep learning medical image analysis](https://theaisummer.com/medical-image-coordinates/)\n- [Introduction to 3D medical imaging for machine learning: preprocessing and augmentations](https://theaisummer.com/medical-image-processing/) ([colab](https://colab.research.google.com/drive/1fyU_YaZUO3B5qVzBJwGoYZ6XVvVLog30?usp=sharing))\n- [Deep learning in MRI beyond segmentation: Medical image reconstruction, registration, and synthesis](https://theaisummer.com/mri-beyond-segmentation/)\n- [Transfer learning in medical imaging: classification and segmentation](https://theaisummer.com/medical-imaging-transfer-learning/)\n- [Introduction to medical image processing with Python: CT lung and vessel segmentation without labels](https://theaisummer.com/medical-image-python/) ([colab](https://colab.research.google.com/drive/1kUOkey3CjWoebA5tVu2oazydFKpJKhrU?usp=sharing) / [repo](https://github.com/black0017/ct-intensity-segmentation) )\n- [3D Medical image segmentation with transformers tutorial](https://theaisummer.com/medical-segmentation-transformers/) ([colab](https://colab.research.google.com/drive/1TdGo33zpX6_KqK1TtGVzBZTRW6SdZsrh?usp=sharing))\n\n### Audio\n\n- [Speech synthesis: A review of the best text to speech architectures with Deep Learning](https://theaisummer.com/text-to-speech/)\n- [Speech Recognition: a review of the different deep learning approaches](https://theaisummer.com/speech-recognition/)\n\n### Biology\n- [Deep learning on computational biology and bioinformatics tutorial: from DNA to protein folding and alphafold2](https://theaisummer.com/deep-learning-biology-alphafold/)\n\n\n## MLOps ([repo](https://github.com/The-AI-Summer/Deep-Learning-In-Production))\n\n### Best practices\n\n- [Deep Learning in Production: Laptop set up and system design](https://theaisummer.com/deep-learning-production/)\n- [Best practices to write Deep Learning code: Project structure, OOP, Type checking and documentation](https://theaisummer.com/best-practices-deep-learning-code/)\n- [How to Unit Test Deep Learning: Tests in TensorFlow, mocking and test coverage](https://theaisummer.com/unit-test-deep-learning/)\n- [Logging and Debugging in Machine Learning - How to use Python debugger and the logging module to find errors in your AI application](https://theaisummer.com/logging-debugging/)\n\n### Data Processing\n\n- [Data preprocessing for deep learning: How to build an efficient big data pipeline](https://theaisummer.com/data-preprocessing/)\n- [Data preprocessing for deep learning: Tips and tricks to optimize your data pipeline using Tensorflow](https://theaisummer.com/data-processing-optimization/)\n\n### Training\n\n- [How to build a custom production-ready Deep Learning Training loop in Tensorflow from scratch](https://theaisummer.com/tensorflow-training-loop/)\n- [How to train a deep learning model in the cloud](https://theaisummer.com/training-cloud/)\n- [Distributed Deep Learning training: Model and Data Parallelism in Tensorflow](https://theaisummer.com/distributed-training/)\n\n### Deployment\n\n- [Deploy a Deep Learning model as a web application using Flask and Tensorflow](https://theaisummer.com/deploy-flask-tensorflow/)\n- [How to use uWSGI and Nginx to serve a Deep Learning model](https://theaisummer.com/uwsgi-nginx/)\n- [How to use Docker containers and Docker Compose for Deep Learning applications](https://theaisummer.com/docker/)\n- [Scalability in Machine Learning: Grow your model to serve millions of users](https://theaisummer.com/scalability/)\n- [Introduction to Kubernetes with Google Cloud: Deploy your Deep Learning model effortlessly](https://theaisummer.com/kubernetes/)\n\n## Libraries tutorials\n\n### JAX ([repo](https://github.com/The-AI-Summer/JAX-examples))\n\n- [JAX for Machine Learning: how it works and why learn it](https://theaisummer.com/jax/)\n- [Build a Transformer in JAX from scratch: how to write and train your own models](https://theaisummer.com/jax-transformer/)\n- [JAX vs Tensorflow vs Pytorch: Building a Variational Autoencoder (VAE)](https://theaisummer.com/jax-tensorflow-pytorch/)\n\n### Tensorflow Extended (TFX)\n\n- [Tensorflow Extended (TFX) in action: build a production ready deep learning pipeline](https://theaisummer.com/tfx/)\n\n### Hugging face\n\n- [A complete Hugging Face tutorial: how to build and train a vision transformer](https://theaisummer.com/hugging-face-vit/) ([repo](https://github.com/The-AI-Summer/Hugging_Face_tutorials))\n\n### Weights and Biases (wandb)\n\n- [A complete Weights and Biases tutorial](https://theaisummer.com/weights-and-biases-tutorial/)\n\n### Einsum and einops\n\n- [Understanding einsum for Deep learning: implement a transformer with multi-head self-attention from scratch](https://theaisummer.com/einsum-attention/) ([repo](https://github.com/The-AI-Summer/self-attention-cv))\n\n### GPU programming\n\n- [Neural Network from scratch-part 1](https://theaisummer.com/Neural_Network_from_scratch/)\n- [Neural Network from scratch-part 2](https://theaisummer.com/Neural_Network_from_scratch_part2/)\n\n## Miscellaneous\n\n- [Document clustering](https://theaisummer.com/Document_clustering/)\n- [Explain Neural Arithmetic Logic Units (NALU)](https://theaisummer.com/NALU/)\n- [How to get hired as a Machine Learning Engineer](https://theaisummer.com/Get_hired_as_a_Machine_Learning_Engineer/)\n- [Apply Machine Learning to your Business](https://theaisummer.com/Machine-Learning-Business)\n\n## Resources\n\n- [Top 10 courses to learn Machine and Deep Learning](https://theaisummer.com/Top_10_courses_to_learn_Machine_and_Deep_Learning/)\n- [Best Artificial Intelligence books to read](https://theaisummer.com/Best-Artificial-Intelligence-books-to-read/)\n- [The Best Machine Learning books to learn AI](https://theaisummer.com/machine-learning-books/)\n- [Best bootcamps and programs to learn Machine Learning and Data Science](https://theaisummer.com/ml-bootcamps/)\n- [Best Resources to Learn Deep Learning Theory](https://theaisummer.com/deep-learning-theory-resources/)\n- [Top Resources to start with Computer Vision and Deep Learning](https://theaisummer.com/computer-vision-resources/)\n- [Best AI and Deep learning books to read in 2022](https://theaisummer.com/deep-learning-books-2022/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthe-ai-summer%2Flearn-deep-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthe-ai-summer%2Flearn-deep-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthe-ai-summer%2Flearn-deep-learning/lists"}