LEAP 2019 – day 4

Notes (not a complete recap today) of day 4 of the LEAP event (day 1, day 2, day 3).

Machine Learning Fundamentals

The real measure how well a ML model is performing is how well it works with data it has never seen. The training phase could use 70% of data and the Test phase the remaining 30%.


More information here: Hackaton Blogpost

Neural Networks are one type of algorithm. Deep Learning is based on Neural Networks.

Activation Function to get the values between 0 and 1 and are an important feature of the neural networks. They basically decide whether a neuron should be activated or not. Whether the information that the neuron is receiving is relevant for the given information or should it be ignored.

More for you to study on:

How do we test a trained RNN model (like the word RNN or the character RNN)? We measure perplexity per word!

“Perplexity is a measurement of how well a probability distribution or probability model predicts a sample. It may be used to compare probability models. A low perplexity indicates the probability distribution is good at predicting the sample.” Source: https://en.wikipedia.org/wiki/Perplexity

Deep Learning requires large datasets. Transfer Learning tries to counter this by taking a different approach by using a big source of data that is already trained (for example from Imagenet). Chop of the last layer and add your own inputs and train from there.

More information: check these out

Introduction to New Azure Machine Learning Service

The Azure Machine Learning Service is brand rew, was released December ’18. It is considered a code first service. You can use one of the deep learning frameworks and transfer into ONNX (Open Neural Network Exchange)

  • TensorFlow
  • PyTorch
  • Scikit-Learn
  • MXNet
  • Chainer
  • Keras

Demo: https://github.com/maxluk/dogbreeds-webinar

AI & Cognitive Services

AI is about amplifying and augmenting human ingenuity. Azure Cognitive Services is here for you if you want to start today. Microsoft offers prebuilt AI for your business: infuse apps, websites and bots with human-like intelligence.

Start AI with ethics (“with great power comes great responsibility”) https://aka.ms/ai-ethics

Demo on AI: https://aidemos.microsoft.com/

Create your own Computer Vision projects: https://customvision.ai

Create a bot in 3 minutes: https://www.qnamaker.ai/

Analyze video content: https://www.videoindexer.ai

Support for 6 key AI capabilities through containers:

  • Key Phrase Extraction
  • Language Detection
  • Sentiment Analysis
  • Face and emotion detection
  • OCR / Text Recognition
  • Language Understanding