Day: October 20, 2019

Three Methods of Data Pre-Processing for Text Classification
AI Natural Language Processing

3 Methods of Data Pre-Processing for Text Classification

Here’s a great article on three techniques for pre-processing raw text input for use in text classification/natural language processing applications. Modern neural networks cannot interpret labeled text as described above and data must be pre-processed before it can be given to a network for training. One straightforward way to do this is with a bag […]

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TensorFlow

O’Reilly Announces Speaker Lineup for Inaugural TensorFlow World

O’Reilly is holding its first-ever TensorFlow World event, presented with TensorFlow at the Santa Clara Convention Center in Santa Clara, California, October 28–31. They’ve just announced the speakers and it looks awesome. Are you going? If so, let us know in the comments. At TensorFlow World, attendees will see TensorFlow 2.0 in action, discover new ways to […]

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Data Driven Neural Networks

Neural Networks from the Ground Up

Speaking neural networks, here’s a live recording of my talk from Azure Data Fest Fall 2019 in Reston In this session, I explain Neural Networks from the Ground Up Neural networks are an essential element of many advanced artificial intelligence (AI) solutions. However, few people understand the core mathematical or structural underpinnings of this concept. […]

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A Beginner’s Guide to Keras: Digit Recognition in 30 Minutes
AI TensorFlow

Beginner’s Guide to Keras: Digit Recognition in 30 Minutes

Here’s a great tutorial on using Keras to create a digit recognizer using the classic MNIST set. An artificial neural network is a mathematical model that converts a set of inputs to a set of outputs through a number of hidden layers. An ANN works with hidden layers, each of which is a transient form […]

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IoT

Explaining Edge Computing

ExplainingComputers explores Edge computing definitions and concepts. This non-technical video focuses on edge computing and cloud computing, as well as edge computing and the deployment of vision recognition and other AI applications. Also introduced are mesh networks, SBC (single board computer) edge hardware, and fog computing.

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AI Mathematics

How To Learn the Math of AI For FREE in 2020

Machine Learning with Phil explores an open source framework for learning the math of artificial intelligence, all for free. Courses mentioned in the video: Calc 1 https://ocw.mit.edu/courses/mathematics/18-01sc-single-variable-calculus-fall-2010/index.htm Calc 2 https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/ Linear Algebra https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/ Differential Equations https://ocw.mit.edu/courses/mathematics/18-03sc-differential-equations-fall-2011/ Stats https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/index.htm Comp Sci https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-005-software-construction-spring-2016/

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Python

Some New Features in Python 3.8

Pretty Printed goes over three new features in Python 3.8: the walrus operation, positional only arguments, and f-strings for debugging. Get the code here: https://prettyprinted.com/l/EeI

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