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Let's say that you do. Now, what is the sentiment that your residents and family members have regarding your communities? Sentiment is important these days. It picks up where the 5-star reviews leave off. It represents what people are actually saying about you.

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. Get your Nordstrom cards out, people. There is a sale going on right now at the beloved retailer, and it's good. I literally shopped the entire sale online, so I can confirm: this is a must-shop event (my bank account is shaking).

I honestly can't understand the multiple 5 star reviews presented on this site about the course. I'm giving it a 1 star which is a bit harsh I know but I'm doing it to offset the number of 5 star reviews here. Honestly I think the course deserves something between 2 and 3 stars depending on your approach to it. Yes Prof. Hinton is a leading expert in the field but the course materials and the way they are presented are pretty bad! I honestly can't understand the multiple 5 star reviews presented on this site about the course.

Voice technology interviews hosted by Carl Robinson. This show brings you the latest research and developments in the field of voice technology, through a series of entertaining, inspirational, and informative conversations with voice technology experts. You'll hear about the latest products and concepts in voice, get new ideas for your own voice projects, and learn about the tools and techniques that will turn those ideas into reality. I conduct interviews with people who've actually implemented voice technologies in a project, including academic researchers, CTOs, engineers and software developers, voice interface designers, product managers, human computer interaction experts and more. We delve into all aspects of voice technology, including the enabling technologies such as speech recognition such as speech-to-text (STT) and speech-to-intent; voice synthesis such as text-to-speech (TTS); transformation of identity/emotion; AI, machine learning and data science related to voice audio; and natural language processing (NLP).

In my previous blog post I wrote about using BeautifulSoup for scraping over two thousand Flixbus customer reviews and identifying company's strengths and weaknesses by performing NLP analysis. Building up on previous story, I decided to use the collected text data to train a Recurrent Neural Network model for predicting customers' sentiment, which proved to be highly efficient scoring 95.93% accuracy on the test set. Without any further ado let's jump into implementation. As a starting point, I loaded a csv file containing 1,780 customer reviews in English with the corresponding rating on the scale from 1 to 5, where 1 is the lowest (negative) and 5 is the highest (positive) rating. Now we have the data to work with.

The second AI ZA meetup was held on 21 June 2016 at Entelect's headquarters in Melrose Arch, Johannesburg. The event was packed with over 50 attendees eager to learn about artificial intelligence and machine learning. The goal of this meetup was to continue with a more in depth classification problem as well as run through the introductory concepts for all those that were new to the meetup. Rishal Hurbans and Hennie Brink gave a short talk on classification algorithms. The uses, advantages, and disadvantages of classification algorithms were covered.