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on
1
Introduction
2
Who am I
3
Context
4
Plan
5
Deployment
6
Rendering Numbers on Screen
7
Creating a System
8
Volume Controller
9
Weights
10
Filters
11
Machine Learning
12
Deep Learning
13
CNTK
14
What is a tensor
15
How does this plugin work
16
Fully trained model
17
Variables
18
Code
19
Dataset
20
Model
21
Running the model
22
Results
23
API
24
Raw API
25
Models
26
Demo
27
Data Set
28
Small subset
29
change model
30
model file
31
model predictions
32
conclusion
33
thank you
Description:
Explore deep learning techniques using Microsoft's Cognitive Toolkit (CNTK) and F# in this 57-minute conference talk. Gain insights into neural networks and their applications in computer vision, speech recognition, and automated language translation. Learn how to train and implement deep learning models within .NET environments. Discover the underlying concepts, including tensors, weights, and filters, while understanding the practical aspects of machine learning deployment. Follow along as the speaker demonstrates creating a system for rendering numbers on screen, implementing volume control, and working with datasets. Dive into code examples, explore the CNTK API, and witness a live demo showcasing model training and prediction. By the end of this talk, acquire the knowledge to leverage F# for effortless model learning and integration into your .NET projects.

Deep Learning with CNTK and F#

NDC Conferences
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