Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Plan Szkolenia
Introduction
- Apache MXNet vs PyTorch
Deep Learning Principles and the Deep Learning Ecosystem
- Tensors, Multi-layer Perceptron, Convolutional Neural Networks, and Recurrent Neural Networks
- Computer Vision vs Natural Language Processing
Overview of Apache MXNet Features and Architecture
- Apache MXNet Compenents
- Gluon API interface
- Overview of GPUs and model parallelism
- Symbolic and imperative programming
Setup
- Choosing a Deployment Environment (On-Premise, Public Cloud, etc.)
- Installing Apache MXNet
Working with Data
- Reading in Data
- Validating Data
- Manipulating Data
Developing a Deep Learning Model
- Creating a Model
- Training a Model
- Optimizing the Model
Deploying the Model
- Predicting with a Pre-trained Model
- Integrating the Model into an Application
MXNet Security Best Practices
Troubleshooting
Summary and Conclusion
Wymagania
- An understanding of machine learning principles
- Python programming experience
Audience
- Data scientists
21 godzin
Opinie uczestników (4)
examples based on our data
Witold - P4 Sp. z o.o.
Szkolenie - Deep Learning for Telecom (with Python)
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Szkolenie - Artificial Neural Networks, Machine Learning, Deep Thinking
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Szkolenie - Introduction to Deep Learning
I was benefit from the passion to teach and focusing on making thing sensible.
