What’s new in Text Analytics for Health?
In this video, Ashly Yeo will demo the exciting announcement made at MS Build about What’s new in Text Analytics for Health.
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Making Data Science Notebooks Collaborative
Jupyter notebook is now one of the most popular tools for data scientists, even though it is fairly difficult to work with it in a team setting. In this talk, explore how notebooks work under the hood and how we can build collaboration features to enable real-time editing.
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Better Web Scraping with Mechanical Soup
I wrote a lot of web scraping libraries back in the day in C#. I had considered porting my library to Python. Python Simplified discusses the benefits of using Mechanical Soup over Beautiful Soup for web scraping.
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Use AutoML in Python with Azure ML Services
-
Frank
- June 26, 2020
- automl python
- Azure
- Azure Machine Learning
- azure machine learning python
- azure machine learning python automl
- azure machine learning service
- azure machine learning service automl
- Azure ML
- azure ml automl
- azure ml automl python
- azure ml python
- azure ml service
- azure ml service automl
- jupyter notebook
- Machine Learning
- Python
- python notebook
Jon Wood shows us how to use AutoML in a Python Jupyter notebook from Azure ML Services. Notebook – https://github.com/jwood803/AzureMLExamples/blob/master/AutoML.ipynb Azure ML Playlist – https://www.youtube.com/playlist?list=PLl_upHIj19Zy88ptd0MQdkxUBb0022-EK
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Data Processing for Neural Network Training with Keras with TensorFlow
-
Frank
- May 27, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- backpropagation
- CNN
- convolution
- Convolutional Neural Network
- CUDA
- cuDNN
- Data
- Deep Learning
- Education
- Educational
- get started
- GPU
- image classification
- jupyter notebook
- Keras
- Machine Learning
- neural net
- Neural Network
- Python
- relu
- Sequential model
- SGD
- stochastic gradient descent
- Supervised Learning
- TensorFlow
- Tensorflow 2.0
- tf.keras
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard demonstrates how to process numerical data that we’ll later use to train our very first artificial neural network in this video.
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TensorFlow and Keras GPU Support – CUDA GPU Setup
-
Frank
- May 21, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- backpropagation
- CNN
- convolution
- Convolutional Neural Network
- CUDA
- cuDNN
- Deep Learning
- Education
- Educational
- get started
- GPU
- image classification
- jupyter notebook
- Keras
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- relu
- Sequential model
- SGD
- stochastic gradient descent
- Supervised Learning
- TensorFlow
- Tensorflow 2.0
- tf.keras
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this video, deeplizard discusses GPU support for TensorFlow and the integrated Keras API and how to get your code running with a GPU.
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Keras Installation and TensorFlow Integration
-
Frank
- May 14, 2020
- .NET
- activation function
- AI
- artificial intelligence
- artificial neural network
- backpropagation
- CNN
- convolution
- Convolutional Neural Network
- cuDNN
- Deep Learning
- Education
- Educational
- get started
- GPU
- image classification
- jupyter notebook
- Keras
- Machine Learning
- neural net
- Neural Network
- Python
- relu
- Sequential model
- SGD
- stochastic gradient descent
- Supervised Learning
- TensorFlow
- Tensorflow 2.0
- tf.keras
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this episode, deeplizard discusses the Keras integration with TensorFlow (tf.keras), compatibility requirements, and how to get Keras installed on your machine!
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Keras Prerequisites – Getting Started with Neural Networks
-
Frank
- May 11, 2020
- .NET
- activation function
- AI
- artificial intelligence
- artificial neural network
- backpropagation
- CNN
- convolution
- Convolutional Neural Network
- cuDNN
- Deep Learning
- Education
- Educational
- get started
- GPU
- image classification
- jupyter notebook
- Keras
- Machine Learning
- neural net
- Neural Network
- Python
- relu
- Sequential model
- SGD
- stochastic gradient descent
- Supervised Learning
- TensorFlow
- Tensorflow 2.0
- tf.keras
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard has put together a course on how to use Keras. In this course, we will learn how to use Keras, a neural network API written in Python! In this episode, we discuss the prerequisites required to start working with Keras, why Keras is a good library to learn, and what resources you’ll have available […]
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Use ML.NET in Python to Create a Linear Regression Model with NimbusML
Jon Wood demonstrates how to use ML.NET within Python by using the NimbusML package. This video also gives an example of creating a linear regression model. Notebook – https://github.com/jwood803/MLNetExamples/blob/master/MLNetExamples/Notebooks/NimbusML/Regression.ipynb NimbusML documentation – https://docs.microsoft.com/en-us/nimbusml/overview
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