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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tensorflow-2-keras-deep-learning-artificial-intelligence-with-python/
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课程名称：Tensorflow 2与Keras：深度学习与人工智能 课程概述：欢迎参加使用Tensorflow 2和Keras API进行深度学习和人工智能的课程。该课程讲解如何使用Tensorflow 2创建深度学习应用程序，并指导学员如何在Google Colab上进行实际操作。课程中包含多个项目，如MNIST数字分类、MNIST时尚数据分类、猫狗图像分类、面部表情识别、叶子病害识别、使用DCGAN（深度卷积对抗网络）生成图像、使用Keras的去噪自编码器等。此外，课程还包括生成式深度学习的神经风格迁移。每节课都附带参考笔记和代码文件。 Tensorflow是一个开源机器学习库，也是深度学习领域使用最广泛的框架之一。谷歌发布了新版本的深度学习库TensorFlow 2，该版本直接集成了Keras API，并将该接口作为平台上深度学习开发的标准接口。 课程内容包括： - 对TensorFlow 2.0（谷歌深度学习框架）的全面理解 - Keras API，以快速构建在Tensorflow 2上运行的模型 - 理解神经网络的工作原理 - 反向传播、前向传播与梯度下降的理解 - 人工神经网络（ANNs） - 卷积神经网络（CNNs） - 使用卷积神经网络进行图像分类和图像识别 - 循环神经网络（RNNs） - 迁移学习 - 使用TensorFlow创建生成对抗网络（GANs） - 自编码器 - 自然语言处理简介 - 使用Numpy、Pandas进行数据分析，以及使用Matplotlib进行数据可视化 该课程为学习深度学习和人工智能提供了实用而深入的知识，使学员能够掌握现代AI技术的基础。
Welcome to Deep Learning and Artificial Intelligence with Tensorflow 2 and Keras API Course.This course includes how to work with tensorflow 2 and creates Deep Learning applications with tensorflow 2 and Keras.This course guide you how to work with google colab, all the hands on work done in google colab.Many Projects included in this course like MNIST Digits Classification, MNIST Fashion data classification, Cat and Dog images Classification, Facial Expression Recognition, Leaf disease recognition, Generate Images with DCGANs(Deep Convolutional Generative Adversarial Networks) with Keras, Denoising autoencoders with Keras, TensorFlow, and Deep Learning etc.Generative Deep Learning - Neural Style Transfer also included in this course.For every lecture reference notes and code file is attached in this course.Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning.Google released a new version of their TensorFlow deep learning library (TensorFlow 2) that integrated the Keras API directly and promoted this interface as the default or standard interface for deep learning development on the platform.This course includes various topics -Complete Understanding of TensorFlow 2.0 (Google's Deep Learning Framework)from the ScratchKeras API to quickly build models that run on Tensorflow 2Learn How Neural Network worksUnderstand Backpropagation, Forward Propogation, Gradient DescentArtificial Neural Networks (ANNs)Convolutional Neural Networks (CNNs)Perform Image Classification with Convolutional Neural NetworksImage RecognitionRecurrent Neural Networks (RNNs)Transfer LearningCreate Generative Adversarial Networks (GANs) with TensorFlowAutoencodersIntroduction to Natural Language ProcessingData Analysis with Numpy, Pandas and Data Visualization with Matplotlib
