PyOhio posted this great talk by Alice Zhao on NLP in Python.

Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. As a data scientist, I often use NLP techniques to interpret text data that I’m working with for my analysis. During this tutorial, I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP.

Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning.

We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.

Setup Instructions
https://github.com/adashofdata/nlp-in-python-tutorial](https://github.com/adashofdata/nlp-in-python-tutorial

Engadget has a first look at Samsung’s robot chef.

Normally when I miss breakfast, it’s by choice. Today, it was because I was in a rush to get to Samsung’s booth on the CES show floor and see if I could get any face time with the company’s cute new rolling robot. (That, uh, didn’t go so great.) The trip was still well worth it, though, because I got to eat a tofu salad partially made by a pair of robotic arms slung from the bottom of some kitchen cabinets.

Read the full story on Engadget.  

In this special episode, Principal Program Manager, Chris Segura, and Forbes Tech Council member, Mike Walker, talk about what they see as the top blockchain trends for 2020 and what they are hearing from companies deploying solutions.

Trend 1: Practical Blockchain Emerges

  • Blockchain is being leveraged in practical use cases today and are expanding in scope and scale over the next three to five years. This also means creating fit for purpose implementations of blockchain. In some cases breaking norms of permissionless blockchains to shift to permissioned blockchains.

    According to the 2019 Gartner CIO Survey, 60% of CIOs expect some kind of blockchain deployment in the next three years. This is also combined with blockchain will be scalable technically, and will support trusted private transactions with the necessary data confidentiality.

Trend 2: Convergence of the Trinity of Digitization (Blockchain + AI + IoT)

  • Blockchain on its own can provide limited value. Focus on the business solutions where blockchain will provide digital differentiation. Leveraging IoT to reach into the physical and analog world, and AI to provide the orchestration and intelligence to data is a symbiotic

Trend 3: Shift to Digital Ecosystems

  • As blockchain becomes a critical part of an organizations digital business transformation journey, blockchain is increasingly used as a critical enabler of digital ecosystems. This is sometimes referred to also as blockchain consortiums. However, digital ecosystems are much more than a consortium.

Links: GE Aviation Story

Related Links:

Follow @CH9 

Follow @MSFTBlockchain

Geofencing has many practical applications. A geofence is a virtual boundary defining an area on a map. Using tools in Azure Maps, Jim demos how to test if a coordinate is inside or outside the Microsoft Redmond campus boundary.

It can be used to send an alert if an expensive piece of machinery leaves a construction site unexpectedly or to send a warning if a worker enters an unsafe location within a factory.

Jim Bennett shows us how to code geofencing applications with Visual Studio, Python, and Azure Maps.

Jim explains why and how to manage a buffer around your geofence boundary. (Hint: GPS is not that accurate!) He also demos how to set a notification using a web hook and an Azure Logic App when a person or item enters or leaves a geofence area.

Next steps:

Step through the tutorial: Set up a geofence by using Azure Maps

Visit Jim’s blog on geofencing: are you where you should be?

Lex Fridman explains that the best way to understand the mind is to build it in the clip from the opening lecture of the MIT Deep Learning lecture series.

Full video: https://www.youtube.com/watch?v=0VH1Lim8gL8

Website: https://deeplearning.mit.edu

This is a clip from the opening lecture of the MIT Deep Learning lecture series.
Full video: https://www.youtube.com/watch?v=0VH1Lim8gL8
Website: https://deeplearning.mit.edu

In October 2019, Google announced its 53-qubit quantum computer named Sycamore had achieved ‘quantum supremacy.’

That’s when quantum computers can complete tasks exponentially more quickly than their classical counterparts.

In this case, Google said its quantum machine completed a task in 200 seconds that would have taken the world’s most powerful computer 10,000 years to complete. IBM, another major player in quantum computing, took issue with the findings.

Either way, it was a big milestone in quantum computing, and it’s leading to a lot of hype in the field. Here’s how quantum computing works, and how it could change everything from Wall Street to Big Pharma and beyond.

Siraj Raval gets back to inspiring people to get into AI and pokes fun at himself.

Almost exactly 4 years ago I decided to dedicate my life to helping educate the world on Artificial Intelligence. There were hardly any resources designed for absolute beginners and the field was dominated by PhDs. In 2020, thanks to the extraordinary contributions of everyone in this community, all that has changed. It’s easier than ever before to enter into this field, even without an IT background. We’ve seen brave entrepreneurs figure out how to deploy this technology to save lives (medical imaging, automated diagnosis) and accelerate Science (AlphaFold). We’ve seen algorithmic advances (deepfakes) and ethical controversies (automated surveillance) that shocked the world. The AI field is now a global, cross-cultural movement that’s not limited to academics alone. And that’s something all of us should be proud of, we’re all apart of this. I’ve packed a lot into this episode! I’ll give my annual lists of the best ML language and libraries to learn this year, how to learn ML in 2020, as well as 8 predictions about where this field is headed. I had a lot of fun making this, so I hope you enjoy it!