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Become proficient with tensor operations in PyTorch. Learn how to build and train linear regression models from scratch, apply logistic regression for classification tasks, and handle data efficiently while optimizing models using gradient descent techniques.
According to Indeed, machine learning engineer salaries currently start at USD 100,809 and top out at just over USD 254,000.
Gain advanced Keras and TensorFlow 2.x techniques you need to build and optimize machine learning models. In this course, practice techniques for deep learning, reinforcement learning, generative models, and sequential data handling that will prepare you to tackle complex real-world challenges.
You’ll begin by learning about Keras's advanced features, including its functional API used to design complex models. You’ll then learn how to create custom layers and models to tailor solutions to unique challenges and seamlessly integrate Keras with TensorFlow 2.x for enhanced functionality.
Next, you’ll use Keras to develop advanced convolutional neural networks (CNNs) that can solve complex computer vision tasks. You’ll apply data augmentation to improve model generalization, implement transfer learning with pre-trained models, and leverage TensorFlow for advanced image processing. You’ll also explore transpose convolution
Then, learn how to build and train advanced Transformers using Keras for sequential data tasks, including time series prediction. You’ll gain hands-on experience developing Transformer-based models for text generation and explore how to utilize TensorFlow to manage sequential data effectively.
Then you’ll dive into unsupervised learning with Keras. You’ll build and train autoencoders, experiment with cutting-edge diffusion models, and develop generative adversarial networks (GANs). You’ll also learn to integrate TensorFlow for advanced unsupervised learning tasks and expand your expertise in generative modeling techniques.
You’ll master advanced Keras techniques for model development by creating custom training loops and optimizing model performance. You’ll explore hyperparameter tuning using Keras Tuner and leverage TensorFlow for enhanced model optimization and custom training workflows.
In the final module, you’ll explore reinforcement learning and its applications in Keras. You’ll implement Q-Learning algorithms and develop deep Q-networks (DQNs) to tackle advanced reinforcement learning tasks, gaining practical experience with this powerful AI technique.
By the end of this course, you’ll have the knowledge and skills to build and optimize advanced models using Keras and TensorFlow 2.x, tackling challenges in computer vision, NLP, reinforcement learning, and generative modeling.
Module 1: Advanced Keras Functionalities
Module 2: Advanced CNNs in Keras
Module 3: Transformers in Keras
Module 4: Unsupervised Learning and Generative Models in Keras
Practice Quiz: GANs and TensorFlow
Module 5: Advanced Keras Techniques
Module 6: Introduction to Reinforcement Learning with Keras
Module 7: Final Project and Assignment
Course Wrap Up
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.