24th October 2019, Thursday
3pm Sydney | 12pm Singapore | 9.30am Mumbai
24th October 2019, Thursday
3pm Sydney | 12pm Singapore | 9.30am Mumbai
Deep Learning has shown tremendous success, but what makes it so special? What are neural networks, and how do they work? What are the differences between popular Deep Learning frameworks like Keras or TensorFlow, and where should you start?
In this webinar, we will apply your convolutional neural network using the ImageNet scenario. We will also review some of the ImageNet architectures and how convolutions work.
We will bring these concepts to life and demonstrate how Databricks simplifies deep learning by letting you quickly access ready to use ML environments as well as prepare data, and train models faster.
After this session, we’ll arm you with the tools you need to run the samples yourself. Attendees will have access to presentations and associated Databricks notebooks.
This is Part of a Deep Learning Series, check out the full series below:
In this webinar, we will apply your convolutional neural network using the ImageNet scenario. We will also review some of the ImageNet architectures and how convolutions work.
We will bring these concepts to life and demonstrate how Databricks simplifies deep learning by letting you quickly access ready to use ML environments as well as prepare data, and train models faster.
After this session, we’ll arm you with the tools you need to run the samples yourself. Attendees will have access to presentations and associated Databricks notebooks.
This is Part of a Deep Learning Series, check out the full series below:
19th Sept - [Part 1] Introducing Neural Networks
3rd Oct - [Part 2] Training your Neural Network
24th Oct - [Part 3] Applying your Convolutional Neural Network
Presenters
Denny Lee
Global Developer Advocate at Databricks
Denny Lee is a Global Developer Advocate at Databricks.
He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premise and cloud environments.
He also has a Masters of Biomedical Informatics from Oregon Health and Sciences University and has architected and implemented powerful data solutions for enterprise Healthcare customers.