搜索资源列表
chapter_1
- tensorflow+python，21个项目玩转深度学习第一章的代码(tensorflow+python 21 projects based on tensorflow and python)
机器人独立PD控制
- 机器人独立pd控制，供新手学习使用，相关说明可在网上查看资料(Robot independent PD control, for beginners to learn to use, the relevant instructions can be viewed online.)
robot-matlab
- 机器智能学习（matlab）机器人自由度旋转关节的运动(Machine intelligent learning (matlab) robot freedom of rotation joint motion)
adaptive-critic-designs-master
- 常用的强化学习中的自适应actor-critic算法python实现教程代码(Commonly used adaptive reinforcement learning actor-critic algorithm Python implementation tutorial code)
DeepMind-Atari-Deep-Q-Learner-master
- 基于python环境的简明深度强化学习深度Q学习实现代码(Concise deep intensive learning based on Python environment and deep Q learning implementation code)
ADRC_Matlab_Simulation
- 非线性自抗扰控制器，仿真通过，可以用来学习和改进(The nonlinear ADRC controller can be used to learn and improve by simulation.)
Q_learning
- 强化学习代码，求解贝尔曼方程，用qlearning求解(Reinforcement learning code, behrman equation, using qlearning solution)
rcnn_car_object_detection
- 基于深度学习的汽车目标检测，所需matlab版本为2017(Deep Learning Based Vehicle Target Detection)
机器学习课件 周志华
- 周志华机器学习课件，哈哈啊啊啊啊啊啊啊啊啊啊啊啊啊啊(Zhou Zhihua machine learning courseware, haha ah ah ah ah ah ah ah ah ah ah ah ah)
Machine_Learning
- 包含了各种机器学习和深度学习的算法，大家互相学习(It contains all kinds of algorithms for machine learning and deep learning, and we learn from each other.)
基于深度学习的汽车目标检测
- 通过使用Matlab软件，实现了基于深度学习的汽车目标检测。(By using Matlab software, vehicle detection based on deep learning is realized.)
matlab q学习 走迷宫
- 在环境中寻找最优路径，自定义出发点和终点，实现智能体与环境交互(Find the optimal path in the environment, customize the starting point and end point, and realize the interaction between the intelligent body and the environment)
Q-learning
- 强化学习的核心算法，Q-table，应用动作值函数对动作的Q值进行更新来找到最优策略。(The core algorithm of reinforcement learning, Q-table, uses action value function to update the Q value of actions to find the optimal strategy.)
入门十大Python机器学习算法（附代码）
- 介绍机器学术十大算法，并且附python实现代码(The ten major algorithms of machine learning are introduced, and the python implementation code is attached.)
Neural-network-and-depth-study-notes
- 简单介绍神经网络基础知识和各重要深度学习流行模型，含有详细的数学推到公式。(A brief introduction to the basic knowledge of neural networks and the important depth of learning popular models, containing detailed mathematical push to the formula.)
Exercise-dp-learning
- 深度学习例子，共五个，逻辑回归，线性回归等等(deep learning examples)
IMM6
- 一种基于扩展的增量流形学习算法IMM-ISOMAP matlab源代码，数据也包含在里面了 (An incremental manifold learning algorithm based on IMM-ISOMAP matlab source code, the data is also included in the)
机器学习
- 用于红酒分类，机器学习，用tensorflow，人工智能小白(For wine classification, machine learning)
LDA_ FDA_with_tutorial
- LDA降维是常用的降维手段之一，是常用的有监督学习降维工具。这个文件对其产生W后的使用进行了简要说明，使用W进行最终的降维可以得到十分漂亮的分析结果（在数据分布符合假设分析的情况下。）(LDA dimension reduction is one of the commonly used dimensionality reduction methods. It is a commonly used supervised learning dimensionality reduction tool
python_self
- 实现了机器学习的各种分类算法，如：knn，svm，朴素贝叶斯，神经网络，决策树等。(Various classification algorithms of machine learning, KNN, SVM, naive bayes, neural network, decision tree, etc.)