Artificial neural network and its applications

Neural NetworksAIWang Yongji

The topic of this course is artificial neural networks and their applications. This article discusses the basic units of artificial neural networks, network structures, several commonly used artificial neural network algorithms and their applications in power systems.

Total of 4 lessons1 hours and 26 minutes and 3 seconds

The cornerstone of machine learning

Machine LearningLin Xuantian

Introduces basic algorithms, theories and practical tools that machine learning users in various fields should know.

Total of 65 lessons15 hours and 29 minutes and 53 seconds

Deep dive into machine learning

Neural NetworksMachine LearningBayesianclustering

(01) Preliminary machine learning and related mathematics (02) Mathematical statistics and parameter estimation (03) Matrix analysis and application (04) Preliminary convex optimization (05) Regression analysis and engineering application (06) Feature engineering (07) Workflow and model Tuning (08) Maximum entropy model and EM algorithm (09) Recommended system and application (10) Clustering algorithm and application (11) Decision tree random forest and adaboost (12) SVM (13) Bayesian method (14) Topic Model (15) Bayesian inference sampling and variation (16) Artificial neural network (17) Convolutional neural network (18) Recurrent neural network and LSTM (19) Caffe&Tensor Flow&MxNet Introduction (20) Bayesian network and HMM (extra Supplement) word embedding word embedding

Total of 21 lessons1 days and 22 hours and 12 minutes and 36 seconds

Artificial Intelligence Jiangxi University of Technology Luo Huilan

AIsearchHeuristic Functionsimulated annealing

Main content: definition of artificial intelligence, tree search algorithm, information-free search strategy, heuristic search strategy, constraint satisfaction problem solving, game algorithm, Bayesian network, hidden Markov model, Kalman filter. ​Features: The teaching time of artificial intelligence courses in the school is 32 hours. It is a required professional course for master's students in computer science and technology. Since the basic theory of artificial intelligence involves intelligent search, reasoning, machine learning, etc., it is an essential theoretical foundation for various research directions of current information graduate students, and can lay a good foundation for students to conduct in-depth research in various directions. The ideas can be applied to pattern recognition, intelligent analysis and processing of images and videos, data mining and intelligent processing applications of various information. Since the course teaching focuses on the description of algorithms, students will not find it boring and can master intelligent ideas well through practical exercises combined with programming.

Total of 40 lessons8 hours and 47 minutes and 20 seconds

Python machine learning applications

PythonMachine Learningsupervised learningUnsupervised Learning

(1) Understand machine learning and introduce classic algorithms by introducing the basic problems of machine learning (classification, clustering, regression, dimensionality reduction); (2) Python third-party library sklearn (scikit-learn), explain how to apply machine learning algorithms to quickly solve problems approach to practical problems.

Total of 27 lessons3 hours and 17 minutes and 52 seconds

Introduction to Information Security (Cryptography)

information securityCryptographyUniversity of Electronic Science and Technology of ChinaLi Hui

Total of 48 lessons1 days and 10 hours and 44 minutes and 43 seconds