Deep learning is a new superpower which will let you build AI systems that just weren't possible a few years ago. It's time to utilize intelligent automation to help your business grow, keep organized, and stay on top of the competition.
This course is for Python developers who haven't worked with machine learning or data science, and want to build intelligent systems right away—without taking a math degree! You will learn about recurrent neural networks, Backprop, SGD, and more. You will work on code examples that are used in a developer's life on a daily basis; you'll not only master the theory, you'll also see how to applied it in the industry as a whole. You will practice all these ideas in MxNet, TensorFlow, Keras, and Gluon. Last but not the least, build Convolutional Neural Networks and apply them to image data. Deep Learning is currently enabling numerous exciting applications in speech recognition, music synthesis, machine translation, natural language understanding, and many others. AI is transforming multiple industries. After finishing this course, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
Target Audience
If you're a Python developer writing any kind of Python app/script, this course will get you working with Deep Learning in Python in no time.
Business Outcomes
- Get up and running with Deep Learning and build complex models layer by layer with increasing complexity
- Explore the art of applying your Deep Learning models to image recognition, Natural Language Processing problems, and voice applications
- Work with TensorFlow, MxNet and higher-level libraries such as Keras and Gluon and understand the full life cycle: defining, training, testing, and deploying your Deep Learning models
