Full Stack Machine Learning - Django REST Framework, React

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Free Download Full Stack Machine Learning - Django REST Framework, React
Published: 2/2025
Created by: Rathan Kumar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 182 Lectures ( 18h 33m ) | Size: 8.88 GB

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