使用 Python 在云中构建和部署机器学习应用程序
- 1 - Introduction
- 1 - Introduction
- 2 - Installing Python
- 2 - Skimage
- 5 - What is Image & Pixels
- 6 - Read Image in skimage
- 7 - Split into rgb array
- 8 - Convert image into grayscale
- 9 - Image Histogram
- 10 - Histogram Equalization
- 11 - Resize Images to any shape
- 3 - Image Data Preparation
- 13 - What we will do
- 14 - Understand the data what we have
- 15 - Get all image filename in list in Python
- 16 - Labeling Images
- 17 - Read all images from the folders and save in Pickle
- 18 - Visualize all images and labels
- 4 - Machine Learning
- 19 - Import Python libraries and Installations
- 20 - Load the Data and split into train and test set
- 21 - HOG Feature Extraction
- 22 - RGB to Gray Transformer
- 23 - HOG Transformer
- 24 - Train SGD classifier
- 25 - Model Evalution
- 5 - Grid Search for Best Hyper parameters
- 26 - Pipeline Model
- 27 - Grid Search for Parameter Tuning
- 28 - Best Estimator
- 6 - Make Pipeline
- 29 - Train Model and Save in pickle
- 30 - Make pipeline Get the Prediction
- 31 - Make pipeline Decision Function
- 32 - Make pipeline pipeline model
- 7 - Image Classification Web App in Flask
- 33 - Install Visual Studio Code
- 35 - Start Flask App
- 36 - Download Bootstrap & JQuery
- 37 - Import Bootstrap 4
- 38 - Navigation Bar
- 39 - Footer
- 40 - Inheritance Layout Page
- 41 - File Upload Http Request
- 42 - Styling the Page with CSS
- 43 - File Upload Backend Operations Flask
- 44 - Integrate Machine Learning Pipeline Model
- 45 - Send Image from HTML to Server Side
- 46 - Adjust the image Height and Width Dynamically
- 47 - Styling HTML for the Output
- 48 - Error Handlers 404 405 500
- 49 - About Page & href
- 8 - Deploy Flask in Python Anywhere
- 50 - Create Account in Python Anywhere for Free
- 51 - Preparing Requirements
- 52 - Upload Flask App in Python Anywhere
- 53 - Installing Requirements
- 54 - Deploy you Flask App and get access anywhere from the World
- 55 - Common Error you will get while deploying the webapp