Training schedule
IN-COMPANY TRAINING PROGRAMS
Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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Learn to create Deep Learning algorithms from the experts
This three-day course covers the fundamentals of Deep Learning and explains how it differs from traditional Machine Learning. Developed by consultants with a proven track record of developing and deploying Deep Learning models at leading, data-driven enterprises, this training delivers the right mix of theory and hands-on practice. You will gain the practical skills you need to implement your own Deep Learning algorithms and learn to apply them to unstructured data, such as images or text.
This training is for you if…
You want to leverage the power of deep learning to solve problems that would be impossible to solve with more traditional ML techniques
You have (some) experience with data science & machine learning
You want a practical course that will teach you to build your own deep learning models
You want to understand enough theory to make the right decisions for your deep learning models
This training is not for you if…
You never work with unstructured data, such as text, images, audio or video and never expect to either
You have no experience with Python or data science whatsoever (check out the Certified Data Science with Python training instead)
You are already familiar with DL basics and want to apply it to a specific data type (check out the Deep Learning Applied to NLP training instead)
You are not interested in applying DL in practice; you’re just here for the maths and theory
Clients we've helped
What you'll learn
During the training
- The history of Deep Learning
- How to determine your network architecture
- How to choose which loss functions to use
- The best structure and way of working for creating your neural network
- Advanced topics within Keras API, such as embedding layers, lambda layers, custom layers, and tensor operations within neural networks
The schedule
- The basics of neural networks (backpropagation, optimizers, activation functions).
- How to use Keras for Deep Learning
- Heuristics to get your network to learn and perform
- Advanced knowledge of Keras API
- Convolutional neural networks with an application for image recognition
- Recurrent neural networks (LSTM, GRU) with an application for time series and NLP
- Final hands-on lab based on participants interest and feedback
After the training you will be able to:
- Build and train your own neural networks with Keras/TensorFlow
- Apply deep learning to a range of different types of data: image, text and time series
- Intuitively understand the theory behind Deep Learning to make the right choices