Build and Deploy Machine Learning App in Cloud with Python

Build and Deploy Machine Learning App in Cloud with Python, available at $54.99, has an average rating of 4.45, with 56 lectures, based on 126 reviews, and has 20083 subscribers.

You will learn about Develop & Deploy Machine Learning Web App in Flask Deploy Flask in Python Anywhere Image Processing with SKIMAGE Feature Extraction with HOG Multiple Image Classification SGD Classifier Hyper parameter tuning with Pipeline Model Basestimator and Transformermixin Flask HTML, CSS cloud deployement Python Anywhere cloud Shell Scripting This course is ideal for individuals who are Anyone who want deploy machine learning web app from scrach or Anyone who want deploy image classification web app from end to end It is particularly useful for Anyone who want deploy machine learning web app from scrach or Anyone who want deploy image classification web app from end to end.

Enroll now: Build and Deploy Machine Learning App in Cloud with Python

Summary

Title: Build and Deploy Machine Learning App in Cloud with Python

Price: $54.99

Average Rating: 4.45

Number of Lectures: 56

Number of Published Lectures: 56

Number of Curriculum Items: 56

Number of Published Curriculum Objects: 56

Original Price: $159.99

Quality Status: approved

Status: Live

What You Will Learn

Develop & Deploy Machine Learning Web App in Flask

Deploy Flask in Python Anywhere

Image Processing with SKIMAGE

Feature Extraction with HOG

Multiple Image Classification

SGD Classifier

Hyper parameter tuning with Pipeline Model

Basestimator and Transformermixin

Flask

HTML, CSS

cloud deployement

Python Anywhere cloud

Shell Scripting

Who Should Attend

Anyone who want deploy machine learning web app from scrach

Anyone who want deploy image classification web app from end to end

Target Audiences

Anyone who want deploy machine learning web app from scrach

Anyone who want deploy image classification web app from end to end

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

Image Processing & classificationis 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 analysisusing scikit image and python.

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

After that we will create web appin 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 !!!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Installing Python

Lecture 3: Download the All Resources

Chapter 2: Skimage

Lecture 1: Download the Resources

Lecture 2: What is Image & Pixels

Lecture 3: Read Image in skimage

Lecture 4: Split into rgb array

Lecture 5: Convert image into grayscale

Lecture 6: Image Histogram

Lecture 7: Histogram Equalization

Lecture 8: Resize Images to any shape

Chapter 3: Image Data Preparation

Lecture 1: Download the Resources

Lecture 2: What we will do ?

Lecture 3: Understand the data what we have

Lecture 4: Get all image filename in list in Python

Lecture 5: Labeling Images

Lecture 6: Read all images from the folders and save in Pickle

Lecture 7: Visualize all images and labels

Chapter 4: Machine Learning

Lecture 1: Import Python libraries and Installations

Lecture 2: Load the Data and split into train and test set

Lecture 3: HOG Feature Extraction

Lecture 4: RGB to Gray Transformer

Lecture 5: HOG Transformer

Lecture 6: Train SGD classifier

Lecture 7: Model Evalution

Chapter 5: Grid Search for Best Hyper parameters

Lecture 1: Pipeline Model

Lecture 2: Grid Search for Parameter Tuning

Lecture 3: Best Estimator

Chapter 6: Make Pipeline

Lecture 1: Train Model and Save in pickle

Lecture 2: Make pipeline – Get the Prediction

Lecture 3: Make pipeline – Decision Function

Lecture 4: Make pipeline – pipeline model

Chapter 7: Image Classification Web App in Flask

Lecture 1: Install Visual Studio Code

Lecture 2: Download the Resources

Lecture 3: Start Flask App

Lecture 4: Download Bootstrap & JQuery

Lecture 5: Import Bootstrap 4

Lecture 6: Navigation Bar

Lecture 7: Footer

Lecture 8: Inheritance (Layout Page)

Lecture 9: File Upload (Http Request)

Lecture 10: Styling the Page with CSS

Lecture 11: File Upload Backend Operations (Flask)

Lecture 12: Integrate Machine Learning Pipeline Model

Lecture 13: Send Image from HTML to Server Side

Lecture 14: Adjust the image Height and Width Dynamically

Lecture 15: Styling HTML for the Output

Lecture 16: Error Handlers 404, 405, 500

Lecture 17: About Page & href

Chapter 8: Deploy Flask in Python Anywhere

Lecture 1: Create Account in Python Anywhere for Free

Lecture 2: Preparing Requirements

Lecture 3: Upload Flask App in Python Anywhere

Lecture 4: Installing Requirements

Lecture 5: Deploy you Flask App and get access anywhere from the World

Lecture 6: Common Error you will get while deploying the webapp

Chapter 9: Bonus Lecture

Lecture 1: Bonus Lecture: Next Steps

Instructors

datascience Anywhere
Team of Engineers

G Sudheer
Instructor

Brightshine Learn
Instructor Team

Rating Distribution

1 stars: 2 votes

2 stars: 3 votes

3 stars: 15 votes

4 stars: 31 votes

5 stars: 75 votes

Frequently Asked Questions

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