Artificial Intelligence Introduction

These consist of particular traits or capabilities that researchers expect an intelligent system to display. Except the textbook, there are several books as the references for making up the detail, such as [artificial intelligence lecture](https://www.cs.sjtu.edu.cn/~linghe.kong/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E8%AE%B2%E4%B9%89%E5%86%AF%E7%BF%94.pdf), [artificial intelligence a modern approach, fourth edition](http://lib.ysu.am/disciplines_bk/efdd4d1d4c2087fe1cbe03d9ced67f34.pdf). A online neural network [example](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.57497&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false) showing how the data work inside the model. [The slides](/files/2025_1_AI/0225_AI_chapter1_overview.pptx) for the first lesson at Feb 25: the overview of artificial intelligence. [The slides](/files/2025_1_AI/0304_AI_chapter2_knowledge.pptx) for knowledge image at March 4. [The slides](/files/2025_1_AI/0311_AI_DeductiveReasoning.pptx) about certain principles at March 11 and 18 am. The experiment [code](/files/2025_1_AI/code/experiment0319_2.py) and input [file](/files/2025_1_AI/code/input1.txt) at March 19 pm. Please finish the [experiment report](/files/2025_1_AI/0319_AI_experimentReport1.docx) before March 26. [The slides](/files/2025_1_AI/0318_AI_uncertaintyReasoning.ppt) on uncertain reasoning at March 18 and 20. [The slides](/files/2025_1_AI/0320_AI_Search.ppt) for searching strategy on March 25. [The experiment](/files/2025_1_AI/0326_AI_AalgorithmReport2.docx) about solving 8 puzzle problem using [A* algorithm](/files/2025_1_AI/0325_AstarAlgorithm_8puzzle.pdf) at March 26, with 3 python codes for [DFS](/files/2025_1_AI/code/experiment0325_3DFS.py), [BFS](/files/2025_1_AI/code/experiment0325_2BFS.py) and [A* algorithm](/files/2025_1_AI/code/experiment0325_4astar.py). [The slides](/files/2025_1_AI/0401_AI_GA.pptx) for genetic algorithm at April 1 am. [The genetic algorithm](/files/2025_1_AI/code/experiment0402GA4.py) experiment and [the report](/files/2025_1_AI/0402_AI_AalgorithmReport3.docx) would be completed on April 2 pm. [The slides](/files/2025_1_AI/0407_AI_PSML.pptx) for expert system and [machine learning](/files/2025_1_AI/0407_AI_ML.pptx) at April 8 am on week 7th. [The linear regression experiment report](/files/2025_1_AI/0409_AI_AalgorithmReport4.docx): [module example](/files/2025_1_AI/code/experiment0409LinearR.py) and [Boston housing prize problem](/files/2025_1_AI/code/experiment0409LinearRBostonHousingPrice.py) with housing [data](/files/2025_1_AI/code/data_collections/housing.csv). [The slides](/files/2025_1_AI/0415_AI_neuralNetwork.pptx) for neural network and [deep learning](/files/2025_1_AI/0415_AI_deepLearning.pptx) on April 15. [Experiment 5](/files/2025_1_AI/0416_AI_logisticRegressionReport5.docx) about logistic regression, including [the breast cancer prediction](/files/2025_1_AI/code/experiment0416LogisticRegress.py) and [the iris classification](/files/2025_1_AI/code/experiment0416LogisticRegressIris.py) using [sklearn](https://scikit-learn.org/) package, a simple logistic regression [example](/files/2025_1_AI/code/experiment0416LogisticRegressPure.py). [Experiment 6](/files/2025_1_AI/0423_AI_KmeansReport6.docx) about Kmeans algorithm [programming code](/files/2025_1_AI/code/experiment0423Kmeans.py). [Experiment 7](/files/2025_1_AI/0430_AI_NeuralNetworkReport7.docx) about neural network [programming code](/files/2025_1_AI/code/experiment0430NN.py). The other [example](/files/2025_1_AI/0430_AI_NN7.pdf) for NN. [Experiment report 8](/files/2025_1_AI/0507_AI_CNNReport8.docx) on [a convolutional neural network coding execution](/files/2025_1_AI/CNN.zip). [0524 Test](/files/0524_test_linearregress.pptx)