Explore the essentials of deep learning through real-world applications. The deep learning (DL) approach to artificial intelligence (AI) has already revolutionized many industries. Learn how these autonomous, self-teaching systems, like Google’s voice and image recognition algorithms, are developed and applied in this dynamic, three-day training. Through hands-on experience, you’ll learn how to leverage cloud GPU resources and build deep-learning models for images, text and time series.
Who should attend Deep Learning training?
- You have experience with data science using Python
- You are proficient with data science tooling (SSH, git, Jupyter Notebook)
- You know the basics of machine learning (ML) and have knowledge of bias versus variance tradeoff, logistic regression, SVM, etc.
Achievements Upon Completion
Through instructor-led discussion and interactive, hands-on exercises, participants will achieve the following outcomes:
You will know:
- The basics of neural networks (backpropagation, optimizers, activation functions, etc.)
- Heuristics to get your network to learn
- Neural network architectures (feedforward, convolutional, recurrent)
You will gain hands-on experience as you:
- Build your own deep learning infrastructure in the cloud
- Debug your models with visualization tools
- Create your own deep learning models for image, text and time series data
- Minimum one year working experience with pandas, scikit-learn, matplotlib, etc. required.
- Please bring your own laptop with Anaconda, SSH and git installed.