Full Stack Machine Learning | Django REST Framework, React

Name: Full Stack Machine Learning | Django REST Framework, React
Rating: 4.5 (242 reviews)

Learn to Build full-fledged Stock Prediction Portal using Python, Django REST Framework, React.js and Machine Learning

Created byRathan Kumar

Last updated 5/2026

English

What you'll learn

REST API Development
Backend Development with Django and Frontend with React JS
Machine Learning with Neural Networks
Deep Learning with LSTM Models
Data Analysis, Data Manipulation and Data Visualization
How to decide which type of machine learning to use for specific problems.
Where deep learning comes in and how neural networks work.
Why a neural network is the best choice for this specific stock prediction use case.
Integration of Machine Learning Models with Web Applications

Course content

25 sections • 187 lectures • 18h 35m total length

Introduction2:08
Build a full stack stock prediction portal using Django REST framework, React, and machine learning with an LSTM architecture to predict stock price movements.
How To Get The Most Out Of This Course0:27
Asking Questions & Getting Help0:27

Django Installation & Starting the Project7:07
Django Rest Framework Installation1:42
Web Application Endpoint8:29
Simple API Endpoint7:24
Create a simple api endpoint at api/v1/students that returns a json response, illustrating public url patterns, json formatting, and the browsable api for development.
Create Model7:00
Manual Serialization7:36
Serializers2:37
Function Based View Get Method11:05
Create a student serializer in serializers.py and a function-based view to get all students using the serializer with many=True, via a DRF API view and the browsable interface.
Storing Data Using Serializers5:55
Get A Single Object Primary Key Based Operation7:16
Update Operation On Student4:58
Delete Operation3:11

Class Based Views Introduction1:55
Explore class based views to handle requests with object oriented principles, mapping get, post, put, and delete to crud operations, boosting code reusability and introducing mixins, generics, and view sets.
Employee Model4:41
Employee Serializer1:31
Class Based View Get All Employees7:12
Class Based Creating Employee4:09
Create a new employee with a post method inside a class-based view, validate data with the employee serializer, and return 201 created or 400 bad request.
Getting Single Object7:16
Update And Delete Employee6:43

Pagination Overview4:53
Global Pagination7:28
Custom Pagination7:42
Create a custom pagination by extending page number pagination, override page size and page query params, and apply it to the employees view to expose next, previous, count, and results.
Filtering7:24
Custom Filter Employee By Designation5:31
Custom Filter Employees By Name And ID7:06
Advanced Filtering7:24
Implement a custom id range filter for employees using Django filters, enabling id min and id max with a custom filter method and label adjustments.
Search Filters7:33
Ordering Filter4:05
Wrapping Up DRF1:09

React.js Introduction0:51
Components And Virtual DOM2:46
Pre-requisite For React0:33
Install Node.js3:36
Create React App Using NPX4:58
Create a React project with npx, learn that npx runs packages temporarily without installation, and compare it to npm while introducing wheat as a faster build tool.
Create React Project With Vite4:47
Directory Structure14:04
Examine the React project directory structure, from root, node_modules, public, to src. Review essential files like eslint, gitignore, and package.json, plus the dev and build scripts.
Edit Default React App3:29
Deleting Default React App5:32

Requirements

Basic knowledge of Python & Django
Basic Knowledge of HTML, CSS and JavaScript

Description

Not just another course, this is a hands-on program where you’ll build a complete, stock prediction portal using Django REST Framework, React.js, and Machine Learning.

Course Flow:

First, you'll learn the fundamentals of Django REST Framework, including what REST APIs are and how to create them. If you're already familiar with Django REST Framework, you can skip this section.
Next, we'll dive into the fundamentals of React.js to build the front-end of our application.
After that, we'll connect Django REST Framework with React.js to build the portal. This will include implementing a user authentication system and other essential features needed for a functional application.
Once the portal structure is ready, it's time to dive into machine learning. This course is not a Machine Learning Bootcamp, so it won’t cover every ML concept in detail. Instead, it takes a practical approach focused on building a stock prediction portal as a real-world use case.

Machine Learning Section:

The basics of machine learning and its different types.
How to choose the right ML approach for a specific problem.
When and why to use deep learning and how neural networks work.
Why a neural network is the best choice for this stock prediction use case.

You'll build an LSTM model in Jupyter Notebook to analyze stock price data and make predictions. Once the model is ready, you’ll create an API to integrate it with the portal and display the results.

This course gives you the full experience of building a real-world stock prediction portal—a full-stack project combining Django REST Framework, React.js, and machine learning.

Additional Skills You'll Learn:

Data manipulation using Pandas and NumPy.
Data visualization using Matplotlib.

By the end of this course, you'll have built a complete project while gaining hands-on experience in both web development and machine learning.

Important Disclaimer: This prediction model should NOT be implemented in real stock market trading. It is developed purely for educational purposes to help you understand the principles of machine learning and stock market data. Relying on this model for actual investments can lead to significant financial risks.

Who this course is for:

Beginner programmers who want to learn how to build web applications using Python, Django & React
Developers with experience in other programming languages who want to transition to Machine Learning
Students who are interested in pursuing a career in full stack machine learning development
Anyone who wants to improve their knowledge of Django and build upon their existing Python skills
Individuals who have some experience with Django but want to level up their skills by building advanced custom projects.

Full Stack Machine Learning | Django REST Framework, React

What you'll learn

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Course content

Introduction3 lectures • 3min

Getting Started4 lectures • 11min

Django REST Framework12 lectures • 1hr 14min

Class Based Views7 lectures • 33min

Mixins3 lectures • 16min

Generics3 lectures • 14min

Viewsets4 lectures • 19min

Nested Serializers5 lectures • 26min

DRF Pagination, Filtering, Search and Ordering10 lectures • 1hr

React.js Introduction & Installation9 lectures • 41min

Requirements

Description

Who this course is for: