- In short, in the universe of pages existing in a (at the time almost) shapeless web, Page and Brin wanted to organize that information to make it become knowledge.
- Out of the more than 200 factors that Google accounts for when deciding whether the content on the web is relevant, RankBrain became the third most relevant.
- First, the semantic web is a set of rules and standards that make human language readable to machines.
- In semantic web jargon an entity is a subject which has unambiguous meaning because it has a strong contextual foundation.
- In other words, instead of going from writing to web writing as unconsciously as the human race transitioned from hunter-gathering to farming, it is time to take this step forward deliberately and intentionally.
When Larry Page and Sergey Brin invented PageRank back in 1996, they had one simple idea in mind: Organize the web based on “link popularity.” In…
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- Since deep learning loves math, we’re going to represent each word as a d-dimensional vector.
- Extracting the rows from this matrix can give us a simple initialization of our word vectors.
- The above cost function is basically saying that we’re going to add the log probabilities of ‘I’ and ‘love’ as well as ‘NLP’ and ‘love’ (where ‘love’ is the center word in both cases).
- One Sentence Summary: Word2Vec seeks to find vector representations of different words by maximizing the log probability of context words given a center word and modifying the vectors through SGD.
- Bonus: Another cool word vector initialization method: GloVe (Combines the ideas of coocurence matrices with Word2Vec)
This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don’t have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you.
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- Aman is working on leveraging the latest developments in Artificial Intelligence (AI) and data science for marketing and sales platforms.
- On this podcast, episode 150, Aman and I discuss how AI functions in account-based marketing (ABM).
- Demandbase found that among 500 B2B marketing executives 80% believe that AI will completely change B2B marketing in the next five years.
- Aman suggests allowing AI to access the available unstructured data via the Internet, noting that it is the new source of truth.
- Listen to the full episode to hear Chris’ prediction of when AI will become mainstream in B2B marketing.
Aman Naimat and Chris Golec from Demandbase discuss the evolving role of Artificial Intelligence in B2B marketing.
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- AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs.
- For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning.
- For more in-depth deep learning applications, the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale.
- Launch instances of the AMI, pre-installed with open source deep learning frameworks (Apache MXNet, TensorFlow, Caffe, Theano, Torch and Keras), to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques; all backed by auto-scaling clusters of GPU-based instances.
- Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of the managed AI services, the AI Platform offerings, and the AI Frameworks you can run on the AWS Cloud.
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning.
Continue reading “AI Tech Talk: An Overview of AI on the AWS Platform”
- To help spur artificial-intelligence research in Montreal, Microsoft will provide a gift of $1 million to McGill University.
- As part of its investment, Microsoft will provide gifts for AI research to the Université de Montréal and to McGill.
- Gift from Microsoft follows company’s planned acquisition of Maluuba
- Microsoft’s gift to McGill “will allow us to recruit and support the best graduate students in this field,” said McGill computer-science professor Joelle Pineau.
- “Thank you to Microsoft for this investment in Montreal’s AI strengths,” said McGill Principal Suzanne Fortier. “
To help spur artificial-intelligence research in Montreal, Microsoft will provide a gift of $1 million to McGill University.
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- A customer leaves an ATM at a Wells Fargo branch in Denver.
- Wells Fargo has been opening up APIs to enable consumers and commercial customers to bank the ways they want to bank.
- Wells Fargo has a startup accelerator investing in young companies focusing on technology such as interactions through natural language and the use of predictive tools.
- By the time the order is up, the customer can use a brand new Wells Fargo credit card to pay.
- 2) Artificial intelligence – Personalization in banking requires the use of sophisticated software to understand as much as possible about the customer in order to serve up recommendations and offers at the right time.
Wells Fargo CEO Tim Sloan lays out the five ways that technology is altering the face of financial services.
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- KDnuggets Home > News > 2015 > Dec > Software > Top 10 Machine Learning Projects on Github ( 15:n41 )
- The following is an overview of the top 10 machine learning projects on Github .
- The importance, and central position, of machine learning to the field of data science does not need to be pointed out.
- The repo has no no software, but if you’re new to Python machine learning, it may be worth checking out.
- Open source software is an important piece of the data science puzzle.
The top 10 machine learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
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