A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！

A collection of pre-trained, state-of-the-art models in the ONNX format

本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/

标注自己的数据集，训练、评估、测试、部署自己的人工智能算法

Public repo for HF blog posts

Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正

仅需Python基础，从0构建大语言模型；从0逐步构建GLM4\Llama3\RWKV6， 深入理解大模型原理

computer vision projects | 计算机视觉相关好玩的AI项目（Python、C++、embedded system）

范仁义录播课资料，会依次推出各种完全免费的前端、后端、大数据、人工智能等课程，课程网站： https://fanrenyi.com ； b站课程地址： https://space.bilibili.com/45664489 ；

梯度下降与Levenberg-Marquardt算法的比较。Comparison of gradient descent and Levenberg–Marquardt algorithm. Сравнение алгоритма градиентного спуска и алгоритма Левенберга-Марквардта.