Build Machine Learning Web Application with Streamlit

Build Machine Learning Web Application with Streamlit, available at $39.99, has an average rating of 4.1, with 12 lectures, based on 5 reviews, and has 18 subscribers.

You will learn about Machine Learning algorithms like Decision Trees, Random Forests Create Machine Learning Web Apps Machine Learning Performance Measures like Confusion Matrix, ROC/AUC, Precision-Recall Curve Crucial Streamlit Commands This course is ideal for individuals who are Data Scientist who want to develop application based on their machine learning models It is particularly useful for Data Scientist who want to develop application based on their machine learning models.

Enroll now: Build Machine Learning Web Application with Streamlit

Summary

Title: Build Machine Learning Web Application with Streamlit

Price: $39.99

Average Rating: 4.1

Number of Lectures: 12

Number of Published Lectures: 12

Number of Curriculum Items: 12

Number of Published Curriculum Objects: 12

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

Machine Learning algorithms like Decision Trees, Random Forests
Create Machine Learning Web Apps
Machine Learning Performance Measures like Confusion Matrix, ROC/AUC, Precision-Recall Curve
Crucial Streamlit Commands

Who Should Attend

Data Scientist who want to develop application based on their machine learning models

Target Audiences

Data Scientist who want to develop application based on their machine learning models

So you are a data scientist who has created great machine learning algorithms in python notebook. Now, you are thinking of developing an application based on that algorithm that can be shared with others or you want to capitalize by selling that application.

Even if you are just starting out in data science, you will reach a point, where you will look to build applications around your model.

Streamlit is the answer to your question, it is an open-source Python library that makes it very easy to create a web application based on machine learning and data for data science. It is easy to learn, you don’t need to understand all the concepts in web programming like HTML, CSS, javascript. Hence, you can build powerful machine learning web apps in a few lines of code at a great speed.

In this course we will cover the following:

1. Introduction to Streamlit

2. Installation of Streamlit

3. Concept of Money Laundering

4. Creating Machine Learning Web App from Scratch

5. Brief description of Machine Learning algorithms like Decision Trees and Random Forests

6. Short Introduction to performance measure of Machine Learning Models like Confusion Matrix, ROC Curve, Precision and Recall Curve

We will gain a lot of useful knowledge from this course. I hope to see you in this course.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Demonstration of Final Product

Chapter 2: Web Application Development

Lecture 1: Installation of Streamlit

Lecture 2: Concept of Money Laundering

Lecture 3: Machine Learning Web Application Part 1

Lecture 4: Machine Learning Web Application Part 2

Lecture 5: Machine Learning Web Application Part 3

Lecture 6: Decision Trees

Lecture 7: Random Forests

Lecture 8: Machine Learning Web Application Part 4

Lecture 9: Performance Metrics for Machine learning Models

Chapter 3: Epilogue

Lecture 1: Thank You !!!

Instructors

Kiran Kumar Shah | FCCA,M.A in Eco,DipIFRS,CAMS,CAMS-AUDIT,CFE,CISA,CISSP
AML/CFT Specialist and Risk Management Expert

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 0 votes
4 stars: 2 votes
5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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