This app can automatically analyze big data classification, regression, and time series.

Use GPT-2 to fine-tune Chinese text and automatically generate Chinese articles.

Use BERT to answer sentence questions, extract fixed feature vectors, and analyze sentence semantics.

GPT-2 is used to automatically generate an English article, and you can also enter any sentence to automatically generate an English article.

Use Python's pySerial package for serial port control.

Use OpenCV functions to analyze connected components of images.

Model conversion, an example of ONNX conversion to OpenVINO.

Use the method of rotating and adjusting the brightness to perform the image augmentation.

Model conversion, an example of Keras conversion to ONNX.

Use the feature comparison method to stitch the images.

Pix2Pix style conversion. Output the original image to the learned image style. For example: convert black and white to color, edge map to photo.

Generate 2D QRcode image.

Adjust the image size in batches.

Recognize fingerprint images.

The MaskRCNN algorithm is used to count and segment image objects, which can be applied to medical image analysis, fish image analysis, biological image analysis, etc.

Generate one-dimensional barcode images of code39 and code128.

PSGAN can be used to apply makeup to a face image.

Test XGBoost uses GPU for training.

Use Support Vector Machine (SVM) to classify Iris flowers.

Examples of reading and writing Excel files.

Examples of reading and writing CSV files.

Read Sin from the file.

Use Python's matplotlib package to generate stock data (opening, closing, highest, lowest) charts.

Read JSON from the file and write JSON to the file.

Use YOLACT to segment the image.

The YOLOv4 solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, etc.

Use UNet to segment the image.

Use 3D ResNets to classify images (videos).

Use 3D UNet to segment the image.

Use LPRNet for license plate recognition.

Use Ganomaly for image anomaly detection.

Use LightGBM to predict housing prices.

Use LightGBM to predict the survival of Titanic passengers.

Use Gradient Boosting to predict housing prices.

Use Gradient Boosting to predict the survival of Titanic passengers.

Use Regression Forest to predict stock prices.

Use Regression Forest to predict the Sin function.

Use Regression Forest to predict stock prices.

Use XGBoost to forecast ticket sales (time series data).

Use XGBoost to predict stock prices.

Use XGBoost to predict the survival of Titanic passengers.

The YOLOv4 Tiny algorithm can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image an

Use LSTM to train and predict the ticket sales.

Use YOLOv4 for real-time multi-object tracking, which can be applied to various fields such as monitoring systems and traffic flow analysis.

Use genetic algorithms to solve the multi-objective scheduling problem.

Use genetic algorithms to solve the problem of factory scheduling Job Shop.

This solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc.

This solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc.

Use genetic algorithm to solve the problem of factory scheduling Flow Shop.

Object detection using MobileNetV3 can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and