Mammoth Club All levels 11 sections 101 lectures

Neural Network Crypto Stock Prediction with Python

Neural Network Crypto Stock Prediction with Python

01
Skill level
All levels
02
Sections
11
03
Lectures
101
04
Instructor
John Bura
What's inside

This course includes.

11
Sections
101
Lectures
101
Resources
Certificate of completion
Included
Mobile and desktop access
Included
AI learning assistance
Included
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Course content

Curriculum & lectures.

3 sections · 14 lectures
+ 01 What is a Neural Network 3 lectures
00A What Is Deep Learning Locked
00B What Is A Neural Network Locked
Source Files Locked
+ 02 Prepare crypto stock data for RNN model 5 lectures
01 Load Ada Token Data Into Colab Locked
02 Build Training And Validation Data For Ml Locked
03 Scale Data With Normalization In Python Locked
04 Build X And Y Data For Neural Network Locked
Source files Locked
+ 03 Build recurrent neural network to predict crypto stock price 6 lectures
01 Build Recurrent Neural Network To Predict Crypto Stock Price Locked
02 Evaluate Rnn Results On Stock Data Locked
03 Visualize Rnn Stock Prediction Results Locked
04 Test Neural Network On New Data Locked
05 Save Nn Ml Model For Future Use Locked
Source files Locked
Description

About this course.

The "Neural Network Crypto Stock Prediction with Python" course is designed to equip you with the knowledge and skills to predict cryptocurrency stock prices using recurrent neural networks (RNNs) in Python. Throughout the course, you will learn how to prepare crypto stock data for the RNN model, load specific cryptocurrency data, and build training and validation datasets for machine learning.

You will explore essential techniques such as data scaling using normalization in Python to ensure the optimal performance of the neural network model. Building on these foundations, you will construct the input and output data (X and Y) for the neural network, enabling you to train the RNN model for crypto stock price prediction.

The course emphasizes hands-on learning as you delve into the process of building a recurrent neural network specifically tailored for predicting cryptocurrency stock prices. By understanding the underlying principles and implementing the RNN model, you will gain practical experience in forecasting crypto stock prices accurately.

Evaluation of RNN results on stock data is a crucial step covered in the course, allowing you to assess the performance and accuracy of the neural network predictions. You will also learn visualization techniques to interpret and present the RNN stock prediction results effectively.

To validate the effectiveness of the model on new data, the course guides you on testing the neural network on unseen cryptocurrency stock data, enabling you to verify the predictive capabilities of the RNN model.

Finally, the course covers the importance of saving the trained neural network model for future use, ensuring that you can leverage your work and continue making accurate predictions.

Don't miss out on this opportunity to gain valuable skills in neural network-based cryptocurrency stock prediction. Enroll in the "Neural Network Crypto Stock Prediction with Python" course today and unlock the potential to make informed investment decisions in the dynamic world of cryptocurrencies. Seize this chance to stay ahead of the market trends and maximize your returns.

Instructors

Taught by people who ship.

John Bura

John Bura

Founder and CEO of Mammoth Club and Course Pro, the #1 AI-powered Learning Management System for course and content development, training and evaluation.

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Neural Network Crypto Stock Prediction with Python

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