dapengsong Goto Github PK

imu_error_state_propagation_doc

采用Hamilton四元数的低成本IMU误差方程详细推导

imucalibration-gesture

calibration for Imu and show gesture

incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

intro2car_p5

ipopt_mpc

udacity MPC

ipyparallel

IPython Parallel: Interactive Parallel Computing in Python

json

JSON for Modern C++

kaggle-quora-solution-8th

kalman

Some Python Implementations of the Kalman Filter from https://blog.csdn.net/weixin_43152152/article/details/115753921

kalman-and-bayesian-filters-in-python

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 filters, and more. All exercises include solutions.

kashgari

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

kbqa-for-diagnosis

knowledge graph, Question answering system，include bilstm-crf, entity normalization, CasRel relation extraction, SlotGate-SLU NLU models , ect..

keras-yolov3-kitti

from https://blog.csdn.net/yangchengtest/article/details/80732237

keras_transfer_cifar10

Object classification with CIFAR-10 using transfer learning

knowledge_graph_demo

本项目用于展示三元组抽取后形成的知识图谱，包括几本小说的实体关系，以及README.md，介绍这方面的一篇文章。

learning-nlp

nlp in action

lego-loam

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

lego-loam_noted

LeGO-LOAM代码注释与学习

lidar-and-point-cloud-1-

传感器数据融合--激光雷达的数据生成以及点云的生成

lidar_localizer

ndt配准 from blog https://www.freesion.com/article/4563869108/

ltslam

lean slam step by step B站杜永全 https://www.bilibili.com/video/BV1J94y1d794?t=73.3

machine-learning

machine learning

machine-learning-notes

周志华《机器学习》手推笔记

machine-learning-notes-1

徐亦达机器学习B站含粒子滤波 https://www.bilibili.com/video/BV1xW411N7f1/?spm_id_from=333.337.search-card.all.click&vd_source=bf1d90c2e3c17b66842fd9f355169565 My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 概率模型和深度学习的讲义(2000+页)和视频链接

machine_learning_python

通过阅读网上的资料代码，进行自我加工，努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

matrix_derivatives

This is a note on matrix derivatives and described my own experience in detail. Hope you'll like it.

ml

Machine Learning

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mlnd_cn_capstone

nd009-cn-advanced-capstone，针对Udacity CN MLND 毕业项目