Learn to apply machine learning to your problems. Follow a complete pipeline including pre-processing and training.
On Completion of this course, you’ll:
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Be able to run deep learning models with Keras on Tensorflow 2 backend
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Understand how to feed own data to deep learning models (i.e. handling the notorious shape mismatch issue)
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Understand Deep Learning with minimal of math
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Understand and code Convolutional Neural Networks as well as graph-based deep models involving residual connections and inception modules
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Get tips on how to use Google’s GPUs to speed up your experiments for free
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Understand and use Keras’ functional API to create models with multiple inputs and outputs
This course is just apt for you in case you:
- Want to learn machine learning (this course is a soft introduction)
- Know machine learning and want to learn deep learning (this course focuses on deep learning)
- Know deep learning but needs help applying their knowledge in practice (this is a very applied course)
- Are comfortable with deep learning models but has trouble processing examples beyond the toy examples covered in typical courses (this course has a real-world case study and not just toy examples)
- Are a researcher or educator working in machine learning and want to move from theory to practice
Some exceptional benefits associated with this course enrolment are:
- Quality course material on Deep Learning with Tensorflow 2 and Keras
- Lifetime access to the course
- Instant & free course updates
- Access to all Questions & Answers initiated by other students as well
- Personalized support from the instructor’s end on any issue related to the course
- Few free lectures for a quick overview
It’s time for you to grab the opportunity and make the most out of this course.
Enroll today!!
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