Artificial intelligence actual combat project (python) + multi-field actual combat training project

Artificial intelligence combat project

Hello everyone, I am Weixue AI. This project will be carried out around artificial intelligence practical projects, which are closely related to life. The practical projects are designed in multiple fields including: finance, education, medical care, geography, biology, humanities, natural language processing, etc.; help Readers combine machine learning and deep learning to build an intelligent and practical artificial intelligence simple system, create influential AI applications, provide the original code of the project, run each line of code step by step, and understand what each line of code is doing. In-depth, and constantly solve problems in multiple fields.

Open source address: https://github.com/shenqiang0601/deep_learning.git

Table of contents

1. The basic part of artificial intelligence

1. Basic part of artificial intelligence 1 - preliminary understanding of artificial intelligence

2. Basic part of artificial intelligence 2-unary linear function perceptron

3. The basic part of artificial intelligence 3-the concept of variance loss function

4. Artificial intelligence basic part 4-gradient descent and backpropagation

5. The basic part of artificial intelligence part 5 - the concept of activation function

6. Basic part of artificial intelligence 6 - preliminary understanding of neural network

7. The basic part of artificial intelligence 7-neural network understanding of high-dimensional space

8. Basic part of artificial intelligence 8-Introduction case of deep learning framework keras

9. Artificial Intelligence Basics Part 9 - In-depth understanding of deep learning

10. Basic part of artificial intelligence 10-Preliminary understanding of convolutional neural network

11. Artificial intelligence basic part 11 - image recognition in practice

12. Basic part of artificial intelligence 12 - preliminary understanding of cyclic neural network

13. The basic part of artificial intelligence 13-LSTM network: predicting the trend of the Shanghai Composite Index

14. Artificial intelligence basic part 14-Application of Monte Carlo method in artificial intelligence and its implementation in Python

15. Artificial intelligence basic part 15-What are data processing upsampling, downsampling and negative sampling in natural language processing?

16. Basic part of artificial intelligence 16-Principle and application of neural network and GPU accelerated training

17. Fundamentals of Artificial Intelligence Part 17-Application of Hidden Markov Model in Sequence Problems

18. Artificial intelligence basic part 18-Application of conditional random field CRF model

...(pending upgrade)

2. Machine Learning Practical Projects

1. Machine learning practice 1- comparison of four algorithms to predict customer credit card repayment

2. Machine learning practice 2-clustering algorithm analysis of Asian football echelons

3. Machine learning practice 3 - use decision tree algorithm to make decisions based on weather data sets

4. Machine Learning Combat 4-Education Field: Visual Analysis and Performance Prediction of Student Achievements-Detailed Analysis

5. Machine Learning Combat 5-Weather Forecast Series: Use datasets to visualize and analyze data and predict the weather conditions of a city

6. Machine learning practice 6-E-commerce website user behavior analysis and service recommendation

7. Machine Learning Practice 7-Customer Value Analysis and Loss Analysis of Waiter Company

8. Machine learning practice 8-Business district analysis based on base station positioning data

9. Machine learning practice 9-automatic identification of car sales tax evasion shops

10. Machine learning practice 10-mining enterprise association rules

...(pending upgrade)

3. Deep Learning Practical Projects

1. Deep learning practice 1-(keras framework) enterprise data analysis and prediction

2. Deep learning practice 2-(keras framework) enterprise credit rating and prediction

3. Deep Learning Practice 3-Text Convolutional Neural Network (TextCNN) News Text Classification

4. Deep Learning Combat 4 - Convolutional Neural Network (DenseNet) Mathematical Graphics Recognition + Topic Pattern Recognition

5. Deep Learning Practice 5-Convolutional Neural Network (CNN) Chinese OCR Recognition Project

6. Deep Learning Combat 6- Convolutional Neural Network (Pytorch) + Cluster Analysis to Realize Air Quality and Weather Prediction

7. Deep learning practice 7-Sentiment analysis of e-commerce product reviews

8. Deep Learning Combat 8-Life Photo Transformation Comic Photo Application

9. Deep learning practice 9-text generation image-local computer realizes text2img

10. Deep learning practice 10-mathematical formula recognition-converting pictures to Latex (img2Latex)

11. Deep learning practice 11 (advanced version) - fine-tuning application of BERT model - text classification case

12. Deep Learning Practice 12 (Advanced Edition) - Using Dewarp to Correct Text Distortion

13. Deep learning practice 13 (advanced version) - text error correction function, good luck for friends who often write typos

14. Deep learning practice 14 (advanced version) - handwritten text OCR recognition, handwritten notes can also be recognized

15. Deep Learning Combat 15 (Advanced Edition) - Let the machine do reading comprehension + you can become a question maker and ask questions

16. Deep learning practice 16 (advanced version) - virtual screenshot recognition text - can do paper contract and form recognition

17. Deep Learning Practice 17 (Advanced Edition) - Construction and Development Case of Intelligent Assistant Editing Platform System

18. Deep Learning Combat 18 (Advanced Edition) - 15 tasks of NLP fusion system, which can realize the NLP tasks you can think of on the market

19. Deep Learning Combat 19 (Advanced Edition) - SpeakGPT's local implementation deployment test, based on ChatGPT to implement SpeakGPT function on your own platform

20. Deep Learning Combat 20 (Advanced Edition) - File Intelligent Search System, which can search for keywords based on file content and quickly find files

21. Deep Learning Practice 21 (Advanced Edition)-AI Entity Encyclopedia Search, an encyclopedia that can be searched for any noun

22. Deep learning practice 22 (advanced version)-AI comic video generation model, make your own comic video

23. Deep Learning Combat 23 (Advanced Edition) - Semantic Segmentation Combat, to achieve the effect of character image matting (computer vision)

24. Deep Learning Combat 24- Artificial intelligence (Pytorch) builds a transformer model, really runs through the transformer model, and deeply understands the structure of the transformer

25. Deep learning practice 25-artificial intelligence (Pytorch) builds T5 model, really runs through the T5 model, and uses the T5 model to generate digital addition and subtraction results

26. Deep Learning Combat 26-(Pytorch) Building TextCNN to realize the task of multi-label text classification

27. Deep learning practice 27-Pytorch framework + BERT to realize the relationship extraction of Chinese text

28. Deep learning practice 28-AIGC project: use ChatGPT to generate customized PPT files

29. Deep Learning Combat 29-AIGC Project: Use GPT-2 (CPU environment) for text continuation and lyrics generation tasks

30. Deep Learning Combat 30-AIGC Project: Automatically Generate Mind Map Files, Free Your Hands

31. Deep learning practice 31-Development of online image recognition tools based on machine learning

...(pending upgrade)

4. Application of Deep Learning Techniques

1. Application of deep learning skills 1 - use knowledge distillation technology for model compression

2. Application of Deep Learning Skills 2-'Residual Connections' in Neural Networks

3. Application of Deep Learning Techniques 3 - Hyperparameter Search in Neural Networks

4. Application of deep learning skills 4-model fusion: voting method, weighted average method, integrated model method

5. Application of deep learning skills 5-model pruning skills in neural networks

6. Application of Deep Learning Techniques 6 - Model Freezing in Neural Networks - Migration Learning Techniques

7. Practical operation of applying 7-K fold cross-validation to deep learning techniques

8. Application of deep learning skills 8- Loading and processing of various data types, and inputting neural network for training

9. Application of Deep Learning Skills 9-Learning rate adjustment in model training and fake data generation skills and summary

10. Application of deep learning skills 10- Construction and application of early stopping method in PyTorch framework

11. Application of Deep Learning Skills 11-Application of sparse parameters and sparse loss function in model training

12. Application of deep learning skills 12-Application of batch normalization in neural network training

13. Application of Deep Learning Skills 13-Principles of Data Parallel Training in Neural Networks

14. Application of Deep Learning Skills 14-Deep Learning Cross-Framework Application, ONNX Realizes Model Interoperability

15. Application of deep learning skills 15-Automatic machine learning Autogluon application skills

...(pending upgrade)

5. Practical project of knowledge map

The beginning of the knowledge graph: the beginning of the actual combat of the knowledge graph-telling what the knowledge graph is and what knowledge to learn.

1. Practical application of knowledge graph 1-construction and visualization application of knowledge graph

2. Practical application of knowledge graph 2-knowledge fusion and knowledge disambiguation of knowledge graph

3. Practical Application of Knowledge Graph 3-Movie Recommendation Algorithm in Knowledge Graph

4. Practical Application of Knowledge Graph 4-Finding Similar Users in Knowledge Graph (Collaborative Filtering Algorithm)

5. Practical application of knowledge graph 5- Create semantic search function based on knowledge graph

6. Practical application of knowledge graph 6-The function of knowledge completion based on knowledge reasoning

7. Practical application of knowledge graph 7-The most complete common Cypher query statement and practical application

8. Practical application of knowledge graph 8- from text relationship extraction to knowledge graph relationship construction process through

9. Practical application of knowledge map 9- knowledge map framework design and class model construction based on neo4j

...(pending upgrade)

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 All the codes, data sets, and models have been sorted out above, and can be run directly. If you need it, please private message me!

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Origin blog.csdn.net/weixin_42878111/article/details/124771186