Udemy - End to End Image Classification Web App Deploy in Cloud

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Project- End to End Machine Learning Web App Deploy in Cloud [TutsNode.com] - Project- End to End Machine Learning Web App Deploy in Cloud 06 Make Pipeline
  • 029 Make pipeline - Get the Prediction.mp4 (140.7 MB)
  • 029 Make pipeline - Get the Prediction.en.srt (20.3 KB)
  • 028 Train Model and Save in pickle.en.srt (18.4 KB)
  • 030 Make pipeline - Decision Function.en.srt (16.6 KB)
  • 031 Make pipeline - pipeline model.en.srt (8.0 KB)
  • 028 Train Model and Save in pickle.mp4 (122.1 MB)
  • 030 Make pipeline - Decision Function.mp4 (99.6 MB)
  • 031 Make pipeline - pipeline model.mp4 (58.6 MB)
04 Machine Learning
  • 020 HOG Feature Extraction.en.srt (17.6 KB)
  • 022 HOG Transformer.en.srt (17.2 KB)
  • 023 Train SGD classifier.en.srt (16.8 KB)
  • 021 RGB to Gray Transformer.en.srt (10.1 KB)
  • 018 Import Python libraries and Installations.en.srt (5.9 KB)
  • 020 HOG Feature Extraction.mp4 (133.2 MB)
  • 019 Load the Data and split into train and test set.en.srt (5.8 KB)
  • 024 Model Evalution.en.srt (5.4 KB)
  • 022 HOG Transformer.mp4 (104.2 MB)
  • 023 Train SGD classifier.mp4 (93.8 MB)
  • 021 RGB to Gray Transformer.mp4 (54.4 MB)
  • 024 Model Evalution.mp4 (38.4 MB)
  • 019 Load the Data and split into train and test set.mp4 (33.7 MB)
  • 018 Import Python libraries and Installations.mp4 (30.3 MB)
02 Skimage
  • 003 Download the Resources.html (0.9 KB)
  • 006 Split into rgb array.en.srt (8.9 KB)
  • 007 Convert image into grayscale.en.srt (8.9 KB)
  • 008 Image Histogram.en.srt (6.5 KB)
  • 004 What is Image & Pixels.en.srt (5.9 KB)
  • 005 Read Image in skimage.en.srt (5.0 KB)
  • 010 Resize Images to any shape.en.srt (5.0 KB)
  • 009 Histogram Equalization.en.srt (4.9 KB)
  • 006 Split into rgb array.mp4 (53.0 MB)
  • 007 Convert image into grayscale.mp4 (53.0 MB)
  • 008 Image Histogram.mp4 (44.0 MB)
  • 009 Histogram Equalization.mp4 (32.6 MB)
  • 005 Read Image in skimage.mp4 (28.2 MB)
  • 010 Resize Images to any shape.mp4 (27.4 MB)
  • 004 What is Image & Pixels.mp4 (20.2 MB)
  • 003 skimage.zip (1.2 MB)
03 Image Data Preparation
  • 017 Visualize all images and labels.en.srt (16.0 KB)
  • 015 Labeling Images.en.srt (10.9 KB)
  • 016 Read all images from the folders and save in Pickle.en.srt (10.3 KB)
  • 012 What we will do _.en.srt (2.6 KB)
  • 014 Get all image filename in list in Python.en.srt (9.9 KB)
  • 013 Understand the data what we have.en.srt (2.9 KB)
  • 011 Download the Resources.html (1.0 KB)
  • 017 Visualize all images and labels.mp4 (85.8 MB)
  • 015 Labeling Images.mp4 (76.0 MB)
  • 014 Get all image filename in list in Python.mp4 (57.1 MB)
  • 016 Read all images from the folders and save in Pickle.mp4 (50.6 MB)
  • 011 dataprepare-machinelearning-pipeline.zip (43.8 MB)
  • 013 Understand the data what we have.mp4 (25.3 MB)
  • 012 What we will do _.mp4 (12.8 MB)
07 Image Classification Web App in Flask
  • 041 File Upload Backend Operations (Flask).en.srt (15.6 KB)
  • 043 Send Image from HTML to Server Side.en.srt (15.3 KB)
  • 042 Integrate Machine Learning Pipeline Model.en.srt (15.3 KB)
  • 046 Error Handlers 404, 405, 500.en.srt (14.1 KB)
  • 039 File Upload (Http Request).en.srt (11.8 KB)
  • 040 Styling the Page with CSS.en.srt (11.8 KB)
  • 036 Navigation Bar.en.srt (9.0 KB)
  • 033 Start Flask App.en.srt (8.3 KB)
  • 044 Adjust the image Height and Width Dynamically.en.srt (7.4 KB)
  • 034 Download Bootstrap & JQuery.en.srt (7.2 KB)
  • 047 About Page & href.en.srt (6.5 KB)
  • 038 Inheritance (Layout Page).en.srt (6.2 KB)
  • 045 Styling HTML for the Output.en.srt (4.3 KB)
  • 037 Footer.en.srt (4.0 KB)
  • 035 Import Bootstrap 4.en.srt (3.2 KB)
  • 032 Download the Resources.html (0.9 KB)
  • 046 Error Handlers 404, 405, 500.mp4 (131.7 MB)
  • 042 Integrate Machine Learning Pipeline Model.mp4 (131.3 MB)
  • 043 Send Image from HTML to Server Side.mp4 (120.1 MB)
  • 041 File Upload Backend Operations (Flask).mp4 (104.6 MB)
  • 040 Styling the Page with CSS.mp4 (64.5 MB)
  • 039 File Upload (Http Request).mp4 (64.5 MB)
  • 044 Adjust the image Height and Width Dynamically.mp4 (61.5 MB)
  • 047 About Page & href.mp4 (55.6 MB)
  • 036 Navigation Bar.mp4 (52.2 MB)
  • 033 Start Flask App.mp4 (43.5 MB)
  • 034 Download Bootstrap & JQuery.mp4 (38.4 MB)
  • 045 Styling HTML for the Output.mp4 (31.5 MB)
  • 038 Inheritance (Layout Page).mp4 (27.6 MB)
  • 037 Footer.mp4 (19.9 MB)
  • 035 Import Bootstrap 4.mp4 (19.1 MB)
  • 032 flask-app.zip (1.7 MB)
05 Grid Search for Best Hyper parameters
  • 026 Grid Search for Parameter Tuning.en.srt (15.3 KB)
  • 025 Pipeline Model.en.srt (8.4 KB)
  • 027 Best Estimator.en.srt (7.3 KB)
  • 026 Grid Search for Parameter Tuning.mp4 (91.1 MB)
  • 025 Pipeline Model.mp4 (49.9 MB)
  • 027 Best Estimator.mp4 (42.0 MB)
08 Deploy Flask in Python Anywhere
  • 052 Deploy you Flask App and get access anywhere from the World.en.srt (10.4 KB)
  • 048 Create Account in Python Anywhere for Free.en.srt (6.9 KB)
  • 049 Preparing Requirements.en.srt (6.4 KB)
  • 053 Common Error you will get while deploying.en.srt (5.0 KB)
  • 050 Upload Flask App in Python Anywhere.en.srt (4.8 KB)
  • 051 Installing Requirements.en.srt (1.5 KB)
  • 052 Deploy you Flask App and get access anywhere from the World.mp4 (80.6 MB)
  • 048 Create Account in Python Anywhere for Free.mp4 (51.6 MB)
  • 049 Preparing Requirements.mp4 (44.9 MB)
  • 053 Common Error you will get while deploying.mp4 (43.0 MB)
  • 050 Upload Flask App in Python Anywhere.mp4 (29.5 MB)
  • 051 Installing Requirements.mp4 (21.7 MB)
01 Introducti

Description


Description

Welcome to Deploy End to End Machine Learning-based Image Classification Web App in Cloud Platform from scratch

Image Processing & classification is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course covers modeling techniques for data preprocessing, model building, evaluation, tuning, and production

We start the course by learning Scikit Image for image processing which is the essential skill required and then we will do the necessary preprocessing techniques & feature extraction to an image like HOG.

After that we will start building the project. In this course you will learn how to label the images, image data preprocessing and analysis using scikit image and python.

Then we will train machine learning here we will see Stochastic Gradient Descenct Classifier for image classification and followed by model evaluation proces and pipeline the machine learning model.

After that we will create web app in Flask by rendering HTML, CSS, Boostrap. Then, we finally deploy web app in Python Anywhere which is cloud platform.

WHAT YOU LEARN ?

Python
Scikit Image
Data Preprocessing
HOG
Base Estimator and TransformerMixIn
SGD Classifier
Create and Make Pipeline Model
Hyperparameter Tuning
Flask
HTTP methods
Deploy in PythonAnywhere

We know that the Image Classification Flask Web App is one of those topics that always leaves some doubts. Feel free to ask question in Q&A, we are happy to answer you question.

I am super excited and see you in the course !!!
Who this course is for:

Anyone who want deploy machine learning web app from scratch
Anyone who want deploy image classification web app from end to end

Requirements

Basic Python Programming
Understanding HTML, CSS, JS

Last Updated 3/2021



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Udemy - End to End Image Classification Web App Deploy in Cloud

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3 GB
seeders:9
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Udemy - End to End Image Classification Web App Deploy in Cloud

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