Description
Welcome to Deploy End to End Machine Learning-based Image Classification Web App in Cloud Platform from scratch
Image Processing and 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 with programming in SKIMAGE which is the essential skill required and then we will do the necessary preprocessing techniques and feature extraction with an image.
Then throughout the course, we will work on the project, providing you with complete training. We will use the powerful functionality built into skimage, sklearn, flask as well as other fundamental libraries such as NumPy, matplotlib, statsmodels.
After that, we will develop the website in Flask and deploy the entire website in Python Anywhere.
With these tools we will master the most widely used models out there:
– Python
– Skimage
– 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 Image Classification Flask Web App is one of those topics that always leaves some doubts.
Until now.
This course is exactly what you need to comprehend once and for all. Not only that, but you will also get a ton of additional materials – notebooks files, course notes – everything is included.
Who this course is for:
- Anyone who want deploy machine learning web app from strach
Requirements
- Basic Python Programming
- Understanding HTML, CSS, JS
Last Updated 3/2021
Download Links
Direct Download
Project- End to End Machine Learning Web App Deploy in Cloud.zip (2.8 GB) | Mirror
Torrent Download
Project- End to End Machine Learning Web App Deploy in Cloud.torrent (81 KB) | Mirror
Source: https://www.udemy.com/course/deploy-image-classification-flask-web-app-in-pythonanywhere/
