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Generative AI, LLM MODELS, Full Stack 15+ Projects

سرفصل های دوره

Core Practical Generative AI, LLM, Javascript Applications for 20X Fast Inference Prototypes. Get Hired: Generative AI


1. All course summary
  • 1.1 webapp.pptx
  • 1. Course Summary
  • 2. React Hooks
  • 3. React DOM
  • 4. React Rest API&Axios
  • 5. Flask Rest API
  • 6. Javascript Basics Concepts
  • 7. Javascript Advance concepts

  • 2. Some Demos
  • 1. WebApp-Object Detection Demo
  • 2. YoloV7 Fast Inference Demo

  • 3. Set up Docker Images,Containers, and Visual Code
  • 1.1 wepapp_state_diagram.drawio.zip
  • 1. Overall Flow State Diagram for Inference Web APP
  • 2. Docker File Configuration
  • 3. Docker Build and Set Up
  • 4. How to Run Docker RUN
  • 5. Configuration of Docker Container with Visual Code

  • 4. Prepare YoloV7 Fast Precision Server Side
  • 1. Yolov7 Start Implementation
  • 2. Yolov7 Server Implementation 2
  • 3. Yolov7 Server Implementation 3
  • 4. Yolov7 Server Implementation 4
  • 5. Yolov7 Server Implementation 5
  • 6. Yolov7 Server Implementation 6

  • 5. Flask Server Implementation for High Security Web App
  • 1. Flask Server Implementation 1
  • 2. Flask Server Implementation 2
  • 3. Flask Server Sign In Implementation
  • 4. Flask Server Registration Implementation

  • 6. Flask Server with YoloV7 Deep Learning Integration
  • 1.1 images.zip
  • 1.2 Images.zip
  • 1.3 models.zip
  • 1. Flask Server & Yolov7 Integration
  • 2. Flask Server & Yolov7 Integration part 2
  • 3. Flask Server & Yolov7 Integration part 3

  • 7. Flask Server Web APP Design
  • 1. Flask Server & Web APP design part 1
  • 2. Flask Web App DL Inference
  • 3. Flask Web App DL Image Inference
  • 4.1 flow diagram for back-end&front-end.drawio.zip
  • 4. Flow Diagram for Back-End&Front-End

  • 8. React Web App Inference with Emotion Detection NLP
  • 1.1 inference web app.drawio.zip
  • 1. Custom Web App Emotion Detection, BERT, Hugging FACE, React JS, Flask, MySql
  • 2.1 cleaning_dataset.drawio.zip
  • 2. How to start for Prototyping Large Language Model with Web APP and Flask
  • 3. BERT & Hugging Face Feature Engineering Part 1
  • 4. Feature Engineering and Preprocessing part 2
  • 5. Feature Engineering and Preprocessing part 3
  • 6. Feature Engineering and Preprocessing part 4

  • 9. Pytorch Dataloader & Hugging Face Framework(Large Language Models)
  • 1. Dataloader,Hugging Face Integration
  • 2. Dataloader,Hugging Face Integration Part 2
  • 3. Dataloader,Hugging Face Integration Part 3

  • 10. BERT NLP Transformer Model Freezing
  • 1. BERT_FINE Part 1

  • 11. Prepare Training and Validation Step with BERT
  • 1.1 models.zip
  • 1. Bert Model Train&Val part 1
  • 2. training part 2
  • 3. train and val part 3
  • 4. Train&Val successful

  • 12. React, Flask, Bert Emotion Inference
  • 1.1 pretrained.zip
  • 1. Pretrained Model Bert and Tokenizer download
  • 2. Where we are and where we have to
  • 3. preprocessing setup
  • 4. Model BackBone setup
  • 5. Model Inference Part 1
  • 6. Model Inference Part 2

  • 13. Flask Server Integration with Model Pretrained
  • 1. Flask Server & Inference Part 1
  • 2. Flask Server & Inference Part 2
  • 3. Flask Server & Inference Part 3

  • 14. React Development Web App
  • 1. React Familiarity
  • 2. React Installation
  • 3. React set up part 1
  • 4.1 emotion_detection.zip
  • 4.2 question-answering.zip
  • 4.3 questions.zip
  • 4. react successful installation
  • 5. Main React Component
  • 6. Evaluate Implementation
  • 7. Emotion Analysis component
  • 8. User FeedBackk Route API
  • 9. Non User Feedback Route API
  • 10. Emotion Analysis Implementation Return
  • 11. Demo Emotion Analysis Successfully Implementated

  • 15. LLM Transformer Based PDF Analizer with React
  • 1.1 presentation.zip
  • 1. Demo Transformer-React
  • 2. React Question Answer Component
  • 3. React Question Answer Component 2
  • 4. LLM Transormer Explanation
  • 5. Flask Route Based Implementation

  • 16. CPlus_Cplus TensorRT Tutorial & Demo
  • 1. CPlus_Cplus TensorRT&Onnx With YoloV4
  • 2. How to implement Onnx Cplus_cplus with YoloV5 Inference
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