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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tensorflow-2-practical/
课程评论：没有评论
课程名称：TensorFlow 2.0 实践 课程概述：人工智能（AI）革命已经到来，TensorFlow 2.0 为实现这一目标提供了更加快速和强大的平台。TensorFlow 2.0 是谷歌最新发布的开源平台，旨在实践中构建和部署人工智能模型。AI 技术正在快速增长，并广泛应用于医疗、国防、银行、游戏、交通和机器人等行业。本课程旨在向学生提供使用 TensorFlow 2.0 和 Google Colab 构建、训练、测试和部署人工神经网络及深度学习模型的实用知识。 课程将提供学生在使用真实世界数据集，通过 TensorFlow 2.0 和 Google Colab 进行人工神经网络和卷积神经网络训练的动手经验。课程内容涵盖多个实际应用项目，包括但不限于： 1. 训练前馈人工神经网络进行回归任务，如销售/收入预测和房价预测。 2. 在医疗领域开发人工神经网络，执行分类任务，如糖尿病检测。 3. 训练深度学习模型进行图像分类任务，如人脸检测、时尚分类和交通标识分类。 4. 开发 AI 模型执行情感分析，分析客户评价。 5. 使用 Tensorboard 进行 AI 模型可视化并评估其性能。 6. 使用 TensorFlow 2.0 Serving 实践部署 AI 模型。 该课程面向希望掌握 TensorFlow 2.0 模型构建和部署基础知识的学生。建议具备基本的编程知识，然而，课程初期将充分讲解相关主题，因此不设先修课程，任何具备基本编程知识的学生均可参加。注册该课程的学生将掌握 AI 和深度学习技术，能够直接利用这些技能解决实际世界中的复杂问题，应用谷歌的全新 TensorFlow 2.0。
Artificial Intelligence (AI) revolution is here and TensorFlow 2.0 is finally here to make it happen much faster! TensorFlow 2.0 is Google's most powerful, recently released open source platform to build and deploy AI models in practice.AI technology is experiencing exponential growth and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries. The purpose of this course is to provide students with practical knowledge of building, training, testing and deploying Artificial Neural Networks and Deep Learning models using TensorFlow 2.0 and Google Colab.The course provides students with practical hands-on experience in training Artificial Neural Networks and Convolutional Neural Networks using real-world dataset using TensorFlow 2.0 and Google Colab. This course covers several technique in a practical manner, the projects include but not limited to:(1) Train Feed Forward Artificial Neural Networks to perform regression tasks such as sales/revenue predictions and house price predictions(2) Develop Artificial Neural Networks in the medical field to perform classification tasks such as diabetes detection.(3) Train Deep Learning models to perform image classification tasks such as face detection, Fashion classification and traffic sign classification.(4) Develop AI models to perform sentiment analysis and analyze customer reviews.(5) Perform AI models visualization and assess their performance using Tensorboard(6) Deploy AI models in practice using Tensorflow 2.0 ServingThe course is targeted towards students wanting to gain a fundamental understanding of how to build and deploy models in Tensorflow 2.0. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master AI and Deep Learning techniques and can directly apply these skills to solve real world challenging problems using Google's New TensorFlow 2.0.
