Description

Step into the fascinating world of deep learning with our Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course. This course takes you through the power of neural networks by using one of the most iconic machine learning challenges—digit recognition. Whether you're brushing up on your AI knowledge or taking your first step into neural networks, this course simplifies the complexity without watering it down.

Expect clear, jargon-free explanations that give neural networks a human touch. Learn how digits are recognised, how machines learn from data, and what goes on inside those layers of artificial intelligence—without sounding like a maths textbook. From data input to prediction output, the entire pipeline is broken down in a logical, structured, and thoroughly digestible way. If you're into machine learning, this project will speak your language—digitally.

Learning Outcomes:

Gain a solid understanding of the principles of deep learning and neural networks.

Learn how to use Google Collab to import and preprocess data for deep learning projects.

Discover how to create your own neural network model to recognise handwritten digits.

Understand how to train your model, make predictions, and evaluate its performance.

Learn how to create your own convolutional neural network model for even more advanced recognition tasks.

The Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network for handwritten digit recognition. Using Google Collab, you'll learn how to import and preprocess data for deep learning projects, create your own neural network model, and train it to recognize handwritten digits with high accuracy. You'll also discover how to evaluate the performance of your model and create a convolutional neural network model for even more advanced recognition tasks.

Deep Learning Projects - Handwritten Digit Recognition Using Neural Network Course Curriculum

Lesson 01: Introduction to Project

Lesson 02: Google Collab

Lesson 03: Importing Packages and Data

Lesson 04: Preprocessing and Model Creation

Lesson 05: Training the Model and Prediction

Lesson 06: Model Creation using CNN

Lesson 07: CNN Model Prediction

How is the course assessed?

Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%.

Exam & Retakes:
It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.
Certification
Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).

CPD

10 CPD hours / points Accredited by CPD Quality Standards

Who is this course for?

Data analysts who want to expand their skills in deep learning and neural networks.

Programmers who want to learn how to build their own neural network models for advanced recognition tasks.

Entrepreneurs who want to develop their own deep learning-based applications.

Students who want to enhance their skills in deep learning and prepare for a career in the field.

Anyone who wants to explore the world of deep learning and neural networks.

Career path

Data Analyst: £24,000 - £45,000

Machine Learning Engineer: £28,000 - £65,000

Software Engineer: £28,000 - £60,000

Technical Lead: £40,000 - £90,000

Chief Technology Officer: £90,000 - £250,000

Certificates

Certificate of completion

Digital certificate - £9

You can apply for a CPD Accredited PDF Certificate at the cost of £9.

Certificate of completion

Hard copy certificate - £15

Hard copy can be sent to you via post at the expense of £15.

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Deep Learning Projects - Handwritten Digit Recognition Using Neural Network Course

By One Education

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