什么是keras
友好的 py 深度学习 lib ，令你快速实现 一个 神经网络
keras 的 作者 是： (François Chollet)[https://twitter.com/fchollet]
keras 是三个 机器学习 lib 的 上层 wrapper
如何安装 keras
就这样：
pip install tensorflow
deeplizard的官方网站
包含了 本系列的 教程
visitMe
https://deeplizard.com/learn/playlist/PLZbbT5o_s2xrwRnXk_yCPtnqqo4_u2YGL
但是 0913 不可访问
他们 youtube channel
深度学习基础
一些简单而清晰的介绍
watchMe
https://www.youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU
keras 实训 视频教程
watchMe
https://www.youtube.com/playlist?list=PLZbbT5o_s2xrwRnXk_yCPtnqqo4_u2YGL
课程目录，以及我的进度
PART 1: 人工神经网络基础训练
Section 1: 介绍keras 和 神经网络
- Processing data
- Building and training neural networks
- Validation and inference
- Saving and loading models
Section 2: 卷积神经网络
- Image processing
- Building and training CNNs
- Using CNNs for inference; @ 2021-09-16 14:19:44
Section 3: 微调 和 迁移学习
- Intro to fine-tuning and VGG16 model
- Implement fine-tuning on VGG16 model
- Using fine-tuned models for inference
- Intro to MobileNet
- Fine-tuning MobileNet on custom data set
Section 4: Additional topics
- Data augmentation
- Keras’ image labeling implementation
- Achieving reproducible results
- Learnable parameters
PART 2: 神经网络模型部署
- Section 1: Deployment with Flask
- Introduction to Flask and web services
- Build a simple Flask app and web app
- Send and receive data with Flask
- Host neural network with Flask
- Build neural network web app to interact with Flask service
- Integrating data visualization with D3, DC, Crossfilter
- Alternative ways to access neural network from Powershell and Curl
- Information privacy and data protection
- Section 2: Deployment with TensorFlow.js
- Introduction to client-side neural networks
- Convert Keras model to TFJS model
- Set up Node.js and Express
- Build UI for neural network web app
- Host a neural network with TFJS
- Explore tensor operations through image processing
- Examine tensor operations with debugger
- Broadcasting tensors
- Efficiency of hosting MobileNet in the browser
