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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-deep-learning-model-deployment/
课程评论：没有评论
课程名称：机器学习深度学习模型部署 课程概述：本课程将教你如何使用各种技术部署机器学习和深度学习模型。课程内容超越模型开发，详细讲解模型如何被不同的应用程序使用，并结合实践示例。 课程结构： 1. 使用Scikit-learn创建分类模型 2. 保存模型和标准缩放器 3. 将模型导出到其他环境 - 本地和Google Colab 4. 使用Python Flask创建本地REST API 5. 在云虚拟服务器上创建机器学习REST API 6. 使用云函数创建无服务器机器学习REST API 7. 使用TensorFlow Serving构建和部署TensorFlow及Keras模型 8. 构建和部署PyTorch模型 9. 使用ONNX将PyTorch模型转换为TensorFlow格式 10. 为PyTorch和TensorFlow模型创建REST API 11. 部署tf-idf和文本分类模型进行Twitter情感分析 12. 使用TensorFlow.js和JavaScript部署模型 13. 使用MLFlow跟踪模型训练实验和部署 14. 在Colab和Databricks上运行MLFlow 15. 附录 - 生成式AI和其他相关主题 - OpenAI及GPT模型的历史 - 创建OpenAI账户并使用Python代码调用文本转语音模型 - 使用Python代码调用OpenAI的聊天完成、文本生成、图像生成模型 - 使用OpenAI API和ChatGPT模型创建聊天机器人，使用Python在Google Colab上实现 - ChatGPT、大语言模型（LLM）及提示工程 本课程将涵盖Python基础和使用Scikit-learn构建机器学习模型的内容，旨在为没有机器学习和深度学习经验的初学者提供指导。课程中还将教授如何使用TensorFlow Keras和PyTorch构建和部署神经网络。部分实验需要Google Cloud（GCP）免费试用账户。
In this course you will learn how to deploy Machine Learning Deep Learning Models using various techniques. This course takes you beyond model development and explains how the model can be consumed by different applications with hands-on examplesCourse Structure:Creating a Classification Model using Scikit-learnSaving the Model and the standard Scaler Exporting the Model to another environment - Local and Google ColabCreating a REST API using Python Flask and using it locallyCreating a Machine Learning REST API on a Cloud virtual serverCreating a Serverless Machine Learning REST API using Cloud FunctionsBuilding and Deploying TensorFlow and Keras models using TensorFlow ServingBuilding and Deploying PyTorch ModelsConverting a PyTorch model to TensorFlow format using ONNXCreating REST API for Pytorch and TensorFlow ModelsDeploying tf-idf and text classifier models for Twitter sentiment analysisDeploying models using TensorFlow.js and JavaScriptTracking Model training experiments and deployment with MLFLowRunning MLFlow on Colab and DatabricksAppendix - Generative AI - Miscellaneous Topics.OpenAI and the history of GPT modelsCreating an OpenAI account and invoking a text-to-speech model from Python codeInvoking OpenAI Chat Completion, Text Generation, Image Generation models from Python codeCreating a Chatbot with OpenAI API and ChatGPT Model using Python on Google ColabChatGPT, Large Language Models (LLM) and prompt engineeringPython basics and Machine Learning model building with Scikit-learn will be covered in this course. This course is designed for beginners with no prior experience in Machine Learning and Deep LearningYou will also learn how to build and deploy a Neural Network using TensorFlow Keras and PyTorch. Google Cloud (GCP) free trial account is required to try out some of the labs designed for cloud environment.
