Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.
Repo of all deep learning models
Data Science, ML & DL Notebooks
Notebooks relevant to our GSERM Summer School lectures and lab course on "Deep Learning: Fundamentals & Applications."
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
In this notebook, we aim to recognize speech commands using classification. For this purpose, we used the SPEECHCOMMANDS dataset and the deep convolutional model M5. The code is written in Python and designed for the PyTorch platform.
This project demonstrates a complete pipeline for weather prediction using a Fully Connected Neural Network (FCNN). The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation.
This project demonstrates a complete pipeline for recognizing handwritten digits using the MNIST dataset. The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation of a Fully Connected Neural Network (FCNN).
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
📚 Jupyter notebook tutorials for OpenVINO™
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
Developed using Python and Google Collab Notebook, this project leverages a Simple Multilayer Perceptron Neural Network (Feed Forward model) for breast cancer prediction. It utilizes the sklearn library for , and model evaluation. The dataset used is the Breast Cancer Wisconsin (Diagnostic) Data Set, Accuracy-95%
This notebook tackles predicting future movements from skeleton data, crucial for applications like fall detection or gesture recognition. Leveraging deep learning, it preprocesses the dataset, trains a CNN model, evaluates its accuracy, and generates predictions for submission, all in a structured manner.
⚡️SwanLab: your ML experiment notebook. 你的AI实验笔记本，跟踪与可视化你的机器学习全流程
✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
Stable Diffusion, SDXL, LoRA Training, DreamBooth Training, Automatic1111 Web UI, DeepFake, Deep Fakes, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, RunPod, NoteBooks, ControlNet, TTS, Voice Cloning, AI, AI News, ML, ML News, News, Tech, Tech News, Kohya LoRA, Kandinsky 2, DeepFloyd IF, Midjourney
The Ultimate Computer Science Notes for Software Engineers and for Inquisitive Minds. 🚀
InsightSolver: Colab notebooks for exploring and solving operational issues using deep learning, machine learning, and related models.
The Deep Learning Notes repository is a comprehensive resource for deep learning enthusiasts, with detailed notebooks, modular implementations and in-depth analysis.
My notebooks on various topics : machine learning, deep learning, image processing, optimization...