Get notified when the Deep Learning for Predictive Analytics course is ready in spring of 2019 and secure your 50% discount on release.
Feedforward Neural Networks
Theory and mathematics behind the basic neural network architecture that lies the foundation for all deep learning applications.
Basic and advanced usage of Google’s Deep Learning library, with emphasis on efficiency and performance.
Learn the necessary data-preprocessing steps like exploration, cleaning, scaling and transformation to make the raw, real-life data sets ready for training.
Efficient Data Input Pipelines
Dealing with large data sets result in a longer training time – even with powerful hardware. Implementation of efficient input pipelines for the input data on the software side may significantly lower the time for the training.
Advanced Training of Deep Learning Models
Learn about the theory and practical implementation of more sophisticated training methods that lower the training time and increase the performance of your Deep Learning models.
Accuracy, recall, specificity, precision, fall-out, miss-rate, etc. – learn how to measure the performance of your models correctly and to interpret the result.
Training in a Web-Cloud
Train the models that you have implemented in a web cloud (Amazon Web Services)
Deployment into Production
Use TensorFlow Serving API, Docker and Kubernetes to deploy the models into a web cloud to make them accessible for your customers – scalable and in real time.
Build a Deep Leaning model to predict the outcome of a banking institution marketing campaign on whether the customer will subscribe a term deposit.
Forecast the volume of drivers and riders at a certain time period in a specific geographic area which maximizes the utilization of drivers and ensures that riders can always get a car whenever and wherever they may need a ride.
Implement a Deep Learning model that identifies fraudulent financial transactions.
Build a recommender system that provides personalized recommendations of an item X for the user Y.
Get access to the exclusive Slack group, stay connected with other students, exchange, get help, create together.
Ask questions and get personal support from the instructor during implementation of your projects.
Optionally, pair up with a fellow student to tackle the course together in order to keep up motivation and work flow.
Classes are limited to 25 students to guarantee the best personal support from the instructor.
Lifelong access to all video content and the Slack group.
30-Days Money Back
If you are not satisfied with the experience you can receive a refund within the first 30 days – no questions asked.
When I began to study Deep Learning I took many excellent online courses on several platforms like Udemy, Udacity and Coursera. Although they provided me with great knowledge about the subject, all courses lacked one particular last step I was looking for: How to apply my knowledge in a real production environment.
I was confident in building Deep Learning models locally, but facing the real world and do the same for customers or employers is a whole different story. In the end, I acquired the necessary skills the hard way by fighting through countless bite-sized pieces of information.
I want to provide a shortcut in learning for those who want to work in this amazing field professionally.
Get notified when Deep Learning for Predictive Analytics is ready in spring of 2019 and to secure your 50% discount on release.