Deep Learning With Tensorflow 2.0, Keras and Python

The "Deep Learning With TensorFlow 2.0, Keras, and Python" course offers a thorough introduction to building and deploying deep learning models using TensorFlow 2.0 and Keras. Covering key topics such as neural network architecture, training techniques, and advanced methods like transfer learning, this course combines theoretical concepts with practical, hands-on projects. By the end, you'll have the skills to develop and optimize deep learning models for real-world applications, making this course ideal for those looking to advance their expertise in the field of artificial intelligence.

Coding Basics

17:31:14 Hours

87 Enrolled

    • (4.53 | 17 Reviews)

English

Last updated

Mon, 29-Jul-2024

Course description

Course Overview

The "Deep Learning With TensorFlow 2.0, Keras, and Python" course provides a comprehensive introduction to deep learning using the latest TensorFlow 2.0 and Keras frameworks. This course covers essential deep learning concepts and techniques, including neural network architecture, training and evaluation, and advanced topics like transfer learning and neural style transfer. Through practical, hands-on projects, you will gain experience building, training, and deploying deep learning models to solve complex problems. Designed for those who want to delve into the field of deep learning, this course combines theoretical knowledge with real-world applications to enhance your expertise.

Key Learning Objectives

  1. Understand Deep Learning Fundamentals: Grasp the core principles of deep learning, including neural networks, activation functions, and loss functions.
  2. Build Neural Networks: Learn to construct, train, and evaluate neural network models using TensorFlow 2.0 and Keras.
  3. Implement Advanced Techniques: Explore advanced deep learning techniques such as transfer learning and neural style transfer.
  4. Optimize Model Performance: Develop skills to fine-tune and optimize models for improved accuracy and efficiency.
  5. Deploy Deep Learning Models: Gain experience in deploying deep learning models to production environments and integrating them into applications.

Requirements

  • Basic Python Knowledge: Familiarity with Python programming, including basic syntax and data structures.
  • TensorFlow Installation: Install TensorFlow 2.0 and Keras (installation instructions provided in the course).
  • Mathematical Foundation: Basic understanding of linear algebra and calculus will be helpful.
  • Machine Learning Basics: Prior knowledge of machine learning concepts is beneficial but not required.
  • Development Environment: A computer capable of running Python and TensorFlow, along with the necessary libraries.

Outcomes

  1. Proficiency in Deep Learning Concepts: Develop a strong understanding of deep learning fundamentals and neural network architectures.
  2. Model Building and Training: Acquire skills to build, train, and evaluate neural networks using TensorFlow 2.0 and Keras.
  3. Advanced Technique Implementation: Implement advanced techniques such as transfer learning and neural style transfer.
  4. Model Optimization: Learn to fine-tune and optimize models to achieve better performance and accuracy.
  5. Deployment Skills: Gain practical experience in deploying and integrating deep learning models into production systems.

Certification

Upon completing the "Deep Learning With TensorFlow 2.0, Keras, and Python" course, you will receive a certificate that validates your expertise in deep learning techniques using TensorFlow and Keras. This certification highlights your ability to build, train, and deploy deep learning models and demonstrates your proficiency in applying advanced deep learning techniques. It serves as a valuable credential for career advancement in data science, machine learning, and artificial intelligence, showcasing your practical skills and theoretical knowledge.

What will i learn?

  • Proficiency in Deep Learning Concepts: Develop a strong understanding of deep learning fundamentals and neural network architectures.
  • Model Building and Training: Acquire skills to build, train, and evaluate neural networks using TensorFlow 2.0 and Keras.
  • Advanced Technique Implementation: Implement advanced techniques such as transfer learning and neural style transfer.
  • Model Optimization: Learn to fine-tune and optimize models to achieve better performance and accuracy.
  • Deployment Skills: Gain practical experience in deploying and integrating deep learning models into production systems.

Requirements

Coding Basics

View profile

Mia Rivera

09-Aug-2024

1

I was disappointed with this course's overall delivery. While it promised a thorough introduction to building deep learning models, the content felt superficial and rushed. The hands-on projects lacked adequate guidance, leaving me confused and frustrated. Additionally, the theoretical concepts were not clearly explained, which hampered my understanding. I expected a more robust learning experience for advancing my skills.

Christopher Clark

09-Aug-2024

5

This course provides an excellent blend of theory and practical application in deep learning. The focus on neural network architecture, training techniques, and transfer learning ensures comprehensive skill development. Engaging hands-on projects prepare you for real-world challenges, making it perfect for advancing expertise in artificial intelligence.

Mia Brown

09-Aug-2024

5

This course provides an excellent blend of theory and practical application, equipping learners with essential skills in neural networks, training methods, and transfer learning, perfect for advancing expertise in artificial intelligence and real-world deep learning solutions.

Sarah Rodriguez

08-Aug-2024

5

An exceptional course that seamlessly blends theory and practice, empowering you to master deep learning and real-world applications effectively!

Joseph Gomez

08-Aug-2024

5

Comprehensive, hands-on learning experience for mastering deep learning and real-world applications in AI. Highly recommend!

David Castillo

08-Aug-2024

5

This course excels in providing a comprehensive foundation in deep learning, seamlessly blending theory with practical projects. Key topics, including neural network architecture and transfer learning, equip learners with essential skills to develop and optimize models for real-world applications, making it ideal for aspiring AI professionals.

Emma Bell

07-Aug-2024

3

This course provides a solid foundation in deep learning, effectively combining theory with hands-on projects, which is essential for real-world applications. The coverage of neural networks, training techniques, and advanced methods like transfer learning is a significant strength. However, it could benefit from more in-depth exploration of model optimization strategies and possibly some case studies to enhance practical understanding further. Overall, it's a valuable resource for advancing AI expertise.

Helen Morgan

06-Aug-2024

5

Exceptional course for mastering deep learning and practical applications!

David Patel

06-Aug-2024

5

An excellent course for mastering deep learning concepts and practical skills using TensorFlow and Keras.

Frank Richardson

06-Aug-2024

5

This course expertly blends theory and hands-on projects, empowering learners to master neural networks and optimize models for real-world AI applications. Highly recommended!

Robert Clark

05-Aug-2024

5

Exceptional course! Comprehensive content, practical projects, and expert instruction equip you with vital skills for real-world deep learning applications. Highly recommended!

Barbara Reyes

05-Aug-2024

3

This course provides an excellent foundation in deep learning, effectively blending theory with hands-on projects. The coverage of neural network architectures and practical training techniques is particularly impressive, as is the focus on advanced methods like transfer learning. However, some sections could benefit from more real-world examples and case studies to enhance understanding. Additionally, more guidance on debugging and optimizing models would further empower learners. Overall, a valuable resource for aspiring AI practitioners!

Patrick Edwards

05-Aug-2024

5

Incredible course! It masterfully blends theory and hands-on projects, empowering learners to excel in deep learning for real-world applications.

Joshua Jones

04-Aug-2024

5

This course expertly blends theory and practice, equipping learners with essential skills in neural networks and advanced techniques. Hands-on projects and real-world applications make it ideal for anyone aiming to deepen their understanding of artificial intelligence.

Michelle Nelson

04-Aug-2024

5

This course exceeded my expectations with its clear, engaging content and practical projects. The blend of theory and hands-on experience ensured I grasped complex concepts easily. The emphasis on advanced techniques like transfer learning provided invaluable skills. I now feel confident tackling real-world AI challenges. Highly recommend!

Susan Williams

04-Aug-2024

5

This course provides an exceptional foundation in deep learning, seamlessly blending theory with practical applications. The comprehensive coverage of neural networks, training techniques, and advanced concepts like transfer learning is impressive. Each hands-on project reinforces learning and boosts confidence in model development. By the end of the course, you'll be equipped with the skills to tackle real-world challenges in artificial intelligence. Highly recommended for anyone eager to enhance their expertise!

David Perez

04-Aug-2024

5

This course is an exceptional gateway to mastering deep learning! It seamlessly blends theoretical knowledge with practical projects, covering crucial topics like neural networks and transfer learning. The hands-on experience prepares you to tackle real-world challenges in artificial intelligence with confidence!

$9.99

$109.99

Lectures

57

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes
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