Packt
Deep Neural Network for Beginners Using Python
Packt

Deep Neural Network for Beginners Using Python

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the basics of training a DNN using the Gradient Descent algorithm.

  • Apply knowledge to implement a complete DNN using NumPy.

  • Analyze and create a complete structure for DNN from scratch using Python.

  • Evaluate and work on a project using deep learning for the IRIS dataset.

Details to know

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Recently updated!

September 2024

Assessments

3 assignments

Taught in English

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There are 5 modules in this course

In this module, we will provide a brief overview of the course and introduce the instructor. We will also outline the learning objectives and what students can expect to achieve by the end of the course.

What's included

3 videos1 reading

In this module, we will delve into the foundational aspects of deep learning. We will start by examining a real-world problem and progressively introduce key concepts such as perceptrons, linear equations, and error functions. This section includes hands-on coding exercises to solidify understanding.

What's included

37 videos

In this module, we will focus on more advanced topics in deep learning. We will cover gradient descent, logistic regression, and the architecture of neural networks. Practical coding sessions will help learners apply these concepts and build their own deep learning models.

What's included

31 videos1 assignment

In this module, we will address optimization challenges in deep learning. Topics include underfitting vs. overfitting, regularization techniques, and strategies to overcome common issues like local minima and vanishing gradients. Learners will gain insights into improving their model's performance and reliability.

What's included

10 videos

In this module, we will undertake a comprehensive final project, applying all the concepts and skills learned throughout the course. Starting with data exploration and progressing through model training and testing, this project will solidify your understanding and ability to implement deep learning solutions.

What's included

5 videos2 assignments

Instructor

Packt
Packt
170 Courses2,469 learners

Offered by

Packt

Recommended if you're interested in Machine Learning

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